automated propagation advice for othr ship detection

Automated propagation advice for OTHR ship detection

R.I.Barnes

Indexing terms: Over-the-horizon radar, Ionospheric refraction, Ship surveillance

Abstract: The ability of an over-the-horizon radar to detect ships is critically dependent on the choice of operating frequency. The author describes an automated surface mode propagation advice system which has been installed into the Jindalee Over-the-Horizon Radar Facility at Alice Springs (23.58, 133.7E). The advice is chiefly derived from backscatter measurements performed by the Jindalee Frequency Management System's Doppler 'miniradar' and includes the optimum operating frequency and a predicted performance indicator for each specific operational radar mission. Global displays of predicted performance, covering the entire surveillance region, are also provided to allow the system to nominate areas where ship detection would be viable with the operational radar. Details on the function, input and output of component modules of the system are included, as well as the basic input data requirements. A sample of the output and diagnostic displays are presented. A €ew limitations to the system performance have been found. These limitations are described along with the future effort that is required to overcome them.

1 Introduction

I . I Background Over-the-horizon radar (OTHR) makes use of the ionospheric refraction of radio waves to provide surveillance over very large areas. Since transmissions from a point source may traverse the entire planet the poten- tial scope of the surveillance region is indeed quite impressive. In reality, the capability is somewhat more modest due to ionospheric limitations. For instance, the Jindalee Facility at Alice Springs (JFAS) is routinely used for surveillance to ranges of 3000km.

Although OTHR is, in some ways, better suited to aircraft detection, it still provides a reasonable capability for wide area surveillance of ships. When providing ship surveillance, an OTHR can be said to be operating in surface mode and it has been found that selection of

OIEE, 1996 ZEE Proceedings online no. 19960153 Paper first received 11th April and in revised form 19th September 1995 The authors are with the High Frequency Radar Division, Defence Science and Technology Organisation, PO Box 1500, Salisbury 5108, Australia

an appropriate operating frequency is crucial for optimising the performance in this mode [l]. Frequency selection using the s,ame techniques as for aircraft mode, e.,p. by minimisiing the ionospheric loss, leads to variable performance because surface mode is more subtly influenced by tlhe propagation and backscatter- ing conditions. The natural phenomena that lead to the relative performances seen in surface mode operations such as ilonospheric multipath and Doppler spread clutter have been studied with the Jindalee OTHR for two decades. However, an automated propagation advice system hLas only recently been developed. This docu- ment surnmarises the Automated Surface Mode propagation Advice system (ASMA) which has been built to assist operations at JFAS by providing optimum frequencies and predicted radar performance indicators.

- T t t e , r power P\. A

Tp & t - 4 0 0.5 1.0 2 5 + 3 0 ><' I

I spread clutter - 4 0 0.5 1.0 2 5 + 3 0

Doppler, Hz 1 I background noise level

Fig. 1 ,Curtoon ojclutter and target Doppler profiles, illustrating the d$ ferences in targets detected in a clutter background as opposed to a noise background Typically, ship targets are slower than air targets and are much more likely to be detected in a clutter background. Note the nonlinear Doppler scale and the effect of system modifications: Modification: Targel. in clutter (surface): Target in noise (air): Increase T ,ower/array No change in SBR Increases SBR

Increases SBR Increase c!:. Can increase SBR Increase BW Increases SBR No change in SBR

Increases SBR Increase R, array Increases SBR A - first-order Bragg scatter B ~ multiple-order scatter C - possible surface and air targets

Like other OTHRs, JFAS is a Doppler radar and hence the Doppler chairacteristics of targets and clutter have to be taken into account when predicting performance. The most important difference between surface and air modes is the radial speed that the targets exhibit. Ships are usually slower and will nearly always have radial speeds less than 25ms-' (-50 knots) and most often under 10msC' (-20 knots). One consequence of this i!j that ship speeds are similar to that of deep ocean waves. The backscattered clutter from these waves is often strong and may even obscure the signal from lairge ships. For surface modes therefore, the optimum frequency at which the OTHR is run depends critically on where the target of interest will appear in Doppler space, relative to the clutter, see Fig. 1.

53 IEE Proc -Radur, Sonar Navig., Vol. 143, No. I , February 1996

Fortunately, the Doppler shifts of clutter from ocean waves have a different wavelength dependence than that of targets and so careful frequency selection can dramatically improve performance for slow ships. Ion- ospherically induced Doppler shifts, higher order Dop- pler components of the ocean clutter and multipath propagation also impact on performance. Frequency selection may improve the performance in these situa- tions as may increasing the transmitted bandwidth. However, there will be a significant amount of time when detection of ships at certain locations is very difficult with simple Doppler sorting. For this reason, it is important that in addition to providing optimum frequencies, that propagation advice also indicates the. viability of proposed surface-mode operations.

In the sections below, many references are made to the instruments of the Jindalee Frequency Management System (FMS). The JFAS miniradar is part of the FMS and is the key tool in providing data for surface- mode advice. Details of the data required from the miniradar are provided below. Other instruments in the FMS include an oblique sounder, which transmits from Darwin (12.4S, 130.9E) to Mt Everard (23.5S, 133.7E) near Alice Springs; a backscatter sounder which is co- located with the miniradar and transmits from Hart’s Range (1 00 km from Mt Everard) and receives backscatter at Mt Everard; and a quasivertical incidence ionogram transmitting directly over the path from Harts Range to Mt Everard. Details on the physical parameters of the devices as well as description of their operational significance can be found in two papers by Earl and Ward [2, 31.

The miniradar is a Doppler backscatter radar. It nominally transmits a 20 kW FMCW waveform through a log periodic antenna and receives on either of two 160m arrays of dual fan monopoles. The arrays are orthogonal and reversible, so that the resultant main beam can be directed to either of four quadrants. The FMCW waveform is repetitive and the miniradar ‘dwells’ coherently for a number of sweeps until the desired Doppler resolution is obtained. The waveform bandwidth is adjustable and is routinely used over the range 2 to 15kHz although larger bandwidths are possible. The monopole array results in a narrow beam of

approximately hll 60 radians where h is the transmit wavelength (in metres) associated with the transmitted frequency, between 5 and 45MHz. The beam can be phased to look in any of eight beams in a geographic quadrant. More details on the miniradar can be found in the Earl and Ward papers.

1.2 Data requirements Data from the JFAS miniradar are the major input required for ASMA. Fig. 2 shows the output of a single miniradar sounding or ‘dwell’. It consists of the backscattered clutter as a function of range and Doppler for a single frequency and azimuth. ASMA assumes that when miniradar dwells are scaled to operational radar sensitivity, by accounting for hardware differences between the two devices, they provide a good indica- tion of what the operational radar would detect in the same region. This assumption is not always accurate. For instance, ionospheric structure may exist within the larger miniradar beam due to small scale structure in E, [4] or the F-region. The F-region ionospheric structure may also be such that weak clutter at non-zero Dop- pler becomes apparent when the sensitivity of measurements is increased from that of the miniradar to the radar. Nevertheless the miniradar provides the basis for the best advice that the FMS can give, and on many occasions the above assumption is expected to be adequate.

To produce surface-mode advice, the miniradar must collect data in the so-called ‘Dopplergram’ mode. In this mode, the miniradar starts transmitting at or above the maximum frequency of interest for the longest surveillance range, and steps down in frequency after each dwell until the lowest frequency of interest is reached. The transmit frequency interval between successive dwells in Dopplergram mode is constrained by compet- ing issues. It is desirable to have good frequency resolution; however the length of time taken to collect the data should be minimised because of the dynamic nature of surface-mode conditions. It is not unusual for advice to be out of date within 10 minutes, and so updates at this rate or better are imperative. If the whole HF band is sampled, then resolution of 2MHz is likely to be reasonable. Correspondingly smaller inter-

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Fig.2 characteristic ocean Bragg scatter returns are visible around I700km 23rd February 1995, 07 11 40, WRF = 5 OHz, BW = lSkHz, Beam = 2 NW, CIT = 25 6s, Range = 1000-3460km (22 893MHz)

54

Mzniradur dwell the image displays the backscatteredpower as a fmction of range and Doppler for a speczjfic waveform frequency and azimuth, the

IEE Proc -Radar Sonar Navig Voi 143 No 1 February 1996

-35 0 35-32 0 32-28 0 28-27 0 27-25 0 25-24 0 24-22 0 22-21 0 21 (knots)

2 0 -2 2 0 -2 2 0 -2 2 0 -2 2 0 -2 2 0 -2 2 0 -2 2 0 - 2 Doppler, Hz 16.28 1798 19.47 2097 22.44 23 89 2542 26.94 R freq, M H z

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Power, dBW/ Doppler ce l l Fig. 3 The frequency resolution of 1.5MHz is a reasonable size increment, however 2MHz would be required for timely advice over the entire HF band. (FMS beam = 4)

Frequency series ojminiradur dwells illustrating the clutter variation as a junction of range, Doppler and frequency

vals may be used over smaller ranges of frequencies. The current sophistication of the system is such that it is seldom useful to use less than a lMHz interval. A series of miniradar dwells collected in Dopplergram mode is shown in Fig. 3. The series covers a limited amount of the HF band, and is for a single miniradar azimuthal beam. The figure illustrates the changes seen in the clutter with a 1.5MHz sounding resolution. In this particular case E, is providing propagation out to around 2300 km and the F-region is providing propagation at larger ranges. The boundaries of the propagation for the two paths is obvious at the higher frequencies, but is overlapped at the lower frequencies. At these frequencies there will be regions, around 2200km, where targets would exhibit multipath charac- teristics.

The Dopplergram data must also cover the range and Doppler extents of interest and be of sufficient resolution to produce advice pertinent to ship detection operations. As a starting point, we state that the range of ship velocities over which advice is required is say, +30 knots. To cover this range, the waveform repeti- tion frequency (WRF) of the FMCW waveform, may then be decreased from 6Hz at a 30MHz transmit frequency, to 1 Hz at 5 MHz. At the lower WRFs, advice update rates are overriding, however, and a lower limit of 2 or 3Hz should be placed on the transmissions. The Doppler resolution is set by the coherent integration time (CIT). To obtain sufficient resolution a CIT of 20 seconds or more is preferable with the above WRFs. With a WRF of 6Hz this is achieved with 128 wave repetitions, while at 2Hz, 64 repetitions is satisfactory. Better resolution provides better advice but the amount of time taken to collect dwells across the HF spectrum becomes too long (>360 s) and the advice becomes stale.

Range resolution varies as the reciprocal of the waveform bandwidth. For surface mode, high range resolution is necessary to improve advice accuracy and so a larger bandwidth is desirable. This has the effect of decreasing the total range coverage, but that is usually of secondary concern. The bandwidth is usually limited by channel availability. In this version of ASMA, a bandwidth of 15kHz is used during the day and lOkHz at night. (It should be noted that at night, even lOkHz clear channels are sometimes rare. This is because of an apparent increase in sensitivity of the radar due to the decreased absorption associated with the nighttime col- lapse of the ionospheric D-region.) The minimum range

IEE Proc -Radar, Sonar Navig , Vol 143, No I February 1996

is readily set by varying the delay of the receiver local oscillator with respect to the transmitted signal, while the maxiinurn range will equal this value plus the product of thie range resolution and the number of range cells. Bandwidths of 1 5 and lOkHz give 10 and 15km resolutions in range respectively. At 5Hz WRF this results in a range coverage of 2500 and 3750km respectively in the JFAS miniradar [5 ] , which is adequate for surveillance from the Australian coast to 3000km from the radar, an average range coverage depth of around 2000km.

In summary, the performance of ASMA is improved with highier resolution measurements in range, Doppler and frequency but this is limited by hardware and advice update rate constraints.

2

As miniradar data are collected, they are subjected to image processing algorithms designed to judge the quality of each dwell. Bad dwells are tagged so they may be excluded from further analysis. A description of the miniradar clean-up algorithms can be found in Barnes et al. [5 ] . After clean-up, dwells considered good are passed on to forrn a series of miniradar dwells. Each dwell consists of R,D, power estimates, where R,, is the number of range cells and D, is the number of FMCW :;weeps, or equivalently, the number of Dop- pler cells. The series consists of Fn of these dwells, where F, is the number of frequencies sampled. In the current JFAS system, only one azimuthal beam can be collected at a time (although extension to simultaneous coverage using eight receivers is in progress). Several beams can still be collected in sequence however, and so in general there exisits Y, frequency series in any one set of advice data, where Y, is the number of beams. Typical values for these parameters are: R, = 250; D, = 128; F, = 12; Y, = 3, and so there exists approximately lo6 power estimates for each set of advice data.

Let the power estimates at this stage be denoted by Pm(r, d, ,f, 4) where 1.he subscript m denotes this a miniradar value and r is range; d is Doppler shift; f is transmit frequency; @ is azimuth.

ASMA operation involves the analysis of these data to produce an optimum frequency, and a predicted radar performance indicator at the optimum frequency, in the region of interest. A reasonably good performance indicator is the predicted excess radar signal-to- background ratio (SBR) of the target. The concept of

Steps to providing surface-mode advice

55

, j/l!zzEz2 1 ionospheric height 10QAm -r 1992 337-06 525Q

4 105

Fig.4 The velocity varies from -20 to +20 knots, within the space that was each miniradar azimuthal ‘beam’ As one would expect the conditions tend to be poorer at low velocities and improve as the absolute value of the velocity increases A precise readout of the excess SBR is available by clicking a mouse on the range, azimuth and velocity of interest Azimuths are measured in degrees from the 324 degree boresite Ionosphenc height = 100km, 2735km (ground), 19 Odeg, velocity = 7 knots, excess SBR = lXdB

Geographic plot of the predicted excess SBR as a fwzction of target velocity for an operational radar of typical sensitivity

Ionospheric height : lOQAk s 1992 337:06:52:5&

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ADVISED FFEWENCY [NHZ]

Fig.5 A precise readout of the frequency is available by clicking on the range, azimuth and velocity of interest. Ionospheric height = 1OOkm; 1965km (ground); 14.1deg; velocity = -10 knots; frequency = 25MHz

Geographic plot of the optimumfrequency as a function of target velocity

an excess SBR is introduced to indicate an excess of SBR over a threshold SBR. The threshold SBR is the minimum SBR an OTHR tracker can successfully work with. SBR is required rather than the usual signal-to-

noise (SNR) because the target may appear in a region of Doppler space where the background may be either clutter or noise. It should be noted that while optimising the SBR maximises the instantaneous detectability,

56 IEE Proc-Radar, Sonar Navig., Vol. 143, No. 1, February 1996

it does nothing to indicate the dynamics of the situa- tion. A rapidly varying Doppler shift may make tracking extremely difficult no matter how easily the target is detected. Stability of conditions is therefore a very important factor in the outcome of any radar surface mission. However this has not been directly addressed in this system due to the complexity that it would add. Fortunately, lack of stability in the first-order Doppler shift is often directly associated with second-order Doppler effects which lead to clutter Doppler smearing. The system is very sensitive to these smearing effects and therefore intrinsically makes some measurement of the stability. Nevertheless an upgraded system would look at a time series of data, to gain direct insight into stability factors.

Let the current advice outputs be denoted as,fqpt the optimum operating frequency and s, the optimum radar excess SBR, where the subscript r indicates this is a radar value.

It is obvious that to move from the power estimates recorded by the miniradar, Pm(r, d , f , g), to the advice outputs that much filtering must be done. The analysis begins with miniradar power being converted into operational radar power by a number of scaling steps involving assumptions on the miniradar to operational radar scaling factors.

pm (T , 4 f , 4) -3 p?- ( T , 4 f , 4) The variable, d, is then changed into target velocity,

v, by subtraction of the first-order Doppler shift and scaling using eqn. 5

By assuming values for the ground and target backscatter coefficients, and the tracking threshold, the dwells can be scaled to excess SBR

p?- ( T , 4 f , 4) -3 PT (T , U, f , 4)

P?-(r, U, f , 4) + S?-(T, U, f , 0)

Fig.6 , G The shading imum radial

zoographic code has velocity

' I I

The r and 4 variables are removed by input of the surveillance area

S T ( T , U, f , 4) + %(U, f ) The v variable is removed by inputting the speed of, or a range of speeds for, the target. Finally, the optimum frequency is chosen bly finding the maximum value, srCfopt), in the remaining function, s,Cf).

3 Propagation advice

The details of the propagation advice algorithms up until the point where the excess SBR is calculated may be found in the Appendix.

3. I SBR function After prlocessing each of the miniradar dwells into equivalent excess SBR, the data remain a function of range, azimuth, target velocity and frequency, i.e.

Plotting 1 he function in a geographic format provides a means of displaying the variation with range and azimuth, but the target velocity and the frequency variations remain. The optiimum frequency can be selected by maxirnising the function at each velocity and geographic position. A four dimensional display then has the ability to plot these data, see Fig. 4. This is described as an excess SBR geographic ship conditions plot. The velocity dependence is plotted across each beam, arid extends from -20 knots to +20 knots. At each velocity the optimum performance is chosen, which means that the optimum frequency is varying across the velocity axis. Fig. 5 shows the optimum frequency variation geographically and against velocity. If an operator is unsure of the radial velocity of the ship,

Propagation advice from target excess

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dot of the predicted conditions for ships in the radial velocity range 5 to 10 knots outbound lot yet been precisely calibrated, but roughly corresponds to a range of exces, SBR of -10 to +20dB Minimum radial T 10 knots, ionospheric height = 100km, 1925km (ground), 20 Rdeg, ship status = 11 1

ieloi :ity = 5 knots; max-

5 1 IEE Psoc.-Radar, Sonar Navig., Vol. 143, No. I , February 1996

or the ship is manoeuvering, then this sort of advice is less optimal than the geographic performance display (see below), which allows the operators to choose a range of velocities. It is expected that the excess SBR display is most useful, for optimising the conditions on ships ‘steaming’ with a known radial speed.

Another way of reducing the data is to obtain operator input of a range of ship velocities of interest. The optimum conditiolis for those velocities can be estimated by an averaging process, and the result displayed geographically, see Fig. 6. The display plots out a colour coded, geographic map of the predicted optimum performance in surface mode for a range of ship speeds, in this case 5 to 10 knots, and overlays the optimum frequency numerically. Ship velocity information is supplied by the operator, using the slider widget on the right-hand side of the display.

These global conditions displays are very important because they provide an ability to nominate areas where detection is viable and hence instigate surface- mode operation in particular regions. However, they do not provide advice for specific radar tasks once an operator has decided to start operations. In a set-up fully integrated with propagation advice for the operational radar, the averaging is extended to the geographic region of the surface-mode operation and the ship velocities of interest. In this case a single optimum frequency and conditions index are automatically made available to the radar to optimise Performance.

3.2 Other displays The displays shown above provide all the performance information necessary to the operator; however several other displays are useful for diagnostic purposes. The clutter frequency series plot, itself a useful display (see Fig. 3 ) , can be extended to be an MDRCS or excess

SBR display. The lower panel of Fig. 7 is a frequency series of the predicted excess SBR. One can now immediately compare the relative merits of different frequencies at particular velocities. The panel above the dwells is an attempt to automatically extract this. For a given velocity range, denoted here by ‘zero Doppler’, (indi- cating a small velocity range centred around zero Dop- pler shift) the relative performance is displayed as a function of frequency and range, for the nominated beam. This display is useful for a quick comparison of a frequency that would be chosen by an operator expert in the interpretation of miniradar data, and the ASMA selected frequency. For a closer look at the action of individual modules, a series of diagnostic displays are useful. The steps that can be more closely looked at include:

The scaling from miniradar to operational radar parameters

First-order Doppler shift removal Scaling to MDRCS Scaling to SBR Scaling to a performance index

Figs. 8 and 9 show an unscaled dwell, along with the product of all the algorithms to the excess SBR stage.

4 Current limitations and future requirements

The performance predicted by ASMA has not yet been fully calibrated against actual radar performance, but initial trials are promising. Detections from a radar mission that successfully used the advice from ASMA in August 1993 are shown in Fig. 10. In this mission the radar was looking at ships cruising south on the Molluca sea.

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Frequency series of clutter dwells converted to ‘SBR dwells’for an OTHR of typical sensitivity excess SBR, dB

Fig.7 Regions of possible detection for given target velocities and locations can be read off and compared for different frequencies. The top panel shows the conditions are good over the ocean where the OHz land clutter is absent or weak. The ship conditions index range of 0 to 12 roughly corresponds to an average excess SBR range of -20 to +30dB

58 IEE Proc -Radar, Sonar Navig , Vol. 143, No. 1, February 1996

3000

2500

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2000

1500

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-20 -15 -10 - 5 O 5 10 15 20 25 30 excess SBR, dB

Fig. 8 Predicted excess SBR

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2 0 -2 Doppler, Hz

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-200 -194 -188 -182 -176 -170 -164 -158 -152 -146 -140 power level , dBW1Doppler cell

Fig.9 Unsealed miniradar data Predicted data is plotted against the same parameter as the unscaled miniradar data of Fig. 8 Note that poorer performance is restricted to where the strong clutter obscures or where there is poor propagation. FMS beam = 5; frequency = 22.436MHz

The ability of the current system to produce good advice is most compromised by the Doppler shift removal algorithm. While the current module is better than 90% effective, the action of this module is so crucial to the production of accurate advice, that this rate is marginal. The Doppler shifts imposed by the ionosphere and by ships are typically of the same order, and so ignoring the ionospheric Doppler shift would make frequency discrimination on the basis of velocity misleading. Discrimination using velocity must be included however because the conditions are so strongly dependent on the velocity of the target. The problems with the Doppler shift removable are generally associated with ionospheric multi-path or very ‘directional’ seas which exhibit only one of the two Bragg reflections. Fig. 11 is an example. Ideas to com- bat these problems are under investigation and include the use of coordinate registration information (see below), and the use of sea state information produced by the operational radar.

inb Fi 10 Azimuth-runyeDoppler plot of returns seen with the operational

The frequenLy of operation was Lhosen using ASMA Several surface targets can be seen at various ranges and azimuths on the edge of the inbound Bragg peak These were, evidently, merc hdnt ships travelling south in the surveillance region

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Poor extrapolation of scaled miniradar can also limit performance. Physical clutter models or empirical models based on radar data are necessary to improve module performance in this case. The problem of scaling and extrapolation is also linked with the problem of miniradar azimuthal sidelobes. Weak sidelobes can appear as useful layers when scaled to operational radar sensitivity, and so it is important to have a miniradar with azimuthal sidelobes as depressed as possible, although in practice it is difficult to suppress sidelobes more than about 25 dB. Alternatively an attempt to deconvolve the antenna pattern from the clutter data might be attempted [6], however sources from all quadrants would have to be sampled.

Several other modules, including the ground backscatter coefficient and ‘ship cross-section modules, pass back default information at the moment. When better estimates of these are calculated, these modules will be updated to reflect this.

Coordinate registration [7] of the advice data, whereby the radar coordinate data (group range and radar azimuth) are converted to ground coordinates (ground range and azimuth) is only very crudely applied a,t the moment. A global knowledge of the propagation paths and the radar to ground coordinate corrections that need be applied would improve this greatly. This information could also be usefully employed by the Doppler shift removal algorithm because the boundaries between paths are often con- spicuous by the discontinuity in Doppler shift.

The staibility of the conditions is another issue that has not been addressedl. If the conditions are changing rapidly, or the first-order Doppler shift is erratic then an OTHFl may have difficulty tracking ships. Currently the advice works on each group of miniradar dwells separately, rather than building a history of advice which would be an indicator of the stability at any one frequency.

IEE ProcRadar, Sonar Navig.. Vol. 143, No. I , February 1996 59

t 3000

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31 0 -31

2200km peak -150 d0W

inbound outbound knots inbound outbound knots

-200 -195 -190 -185 -180 -175 -170 -165 -160 -155 -150 clutter level, dBWlDoppler cell

Fig. 11 The pioblem IS lilcely to be related to the large difference in power between the Incoming and outgoing Bragg scatter WRF = 5 OHz, BW = lSkHz, beam = 1, CIT = 25 6s, range = 1000-3460km, frequency = I8 873MHz

iMNziradar power dwell where the Doppler shlft removal algorithm llas failed in removing the first-order Doppler estimate

5 Summary

Details of an automated OTHR surface-mode propagation advice system, ASMA, have been presented, and the modules necessary to provide this advice have been described. Modules, where the performance of algorithms are problematic and in need of further development, have been identified. Displays for providing advice and diagnostic data have been detailed.

Certain hardware requirements are critical for good performance of a surface-mode advice system. It is important to have an externally noise-limited, mul- tichannel Doppler radar system with an update rate of about five minutes. The radar must have the capability of collecting high resolution backscatter data with WRF’s as low as 2Hz. Radar azimuthal sidelobes confuse advice algorithms and must be kept to a minimum or deconvolved from the data.

6 Acknowledgments

The author would like to thank Mr Stephen Hutchin- son whose dedication allowed this work to reach frui- tion much earlier than it would otherwise have done, and Dr. P. Whitham who provided useful comments and criticisms.

7 References

1

2

BARNUM, J.R.: ‘Ship detection with high-resolution HF sky- wave radar’, IEEE J. Ocean. Eng., 1986, OE-11, (2), pp. 196-209 EARL, G.F., and WARD, B.D.: ‘Frequency management sup- port for remote sea-state sensing using the Jindalee radar’, IEEE J . Ocean. Eng., 1986, OC11, (2), pp. 164-173

3 EARL, G.F., and WARD, B.D.: ‘The frequency management system of the Jindalee over-the-horizon backscatter HF radar’, Radio Sei., 1987, 22, (2), pp. 275-291

4 BARNES, R.I . : ‘Analysis of E,y traces from a calibrated oblique ionosonde’, J. Atmos. Terr. Phys., (accepted for publication)

5 BARNES, R.I. , ROBERTS, S.L., and WHITHAM, P.S.: ‘Clean- up algorithms for the JFAS mini-radar’, SRL technical report

FROM, W.R., and WHITEHEAD, J.D.: ‘The calibration of an HF radar used for ionospheric research’, Radio Sei., 1984, 19. (1). pp. 423-428

SRL-0134-TR, DSTO, 1993 6

60

7 McNAMARA. L.F.: ‘The ionosohere: communications. surveillance and direction finding’ (Orb&, Krieger Publishing Company, Melbourne, Florida, 1991)

8 BOOKER, H.G.: ‘Use of scintillation theorv to exdain frequency-spread on F-region ionograms’, J. Atmos. Teb . Phys., 1986, 48, pp. 327

9 DAVIES, K.: ‘Ionospheric radio waves’ (Peter Peregrinus Ltd., London, UK, 1990)

10 BARRICK, D.E., HEADRICK, J.M., BOGLE, R.W., and CROMBIE, D.D.: ‘Sea backscatter a t HF: interpretation and uti- lisation of the echo’, Proc. IEEE, 1974, 62, pp. 673-680

8 Appendix

8.7 Scaling miniradar dwells to operational radar sensitivity ASMA has been designed to have the capability of predicting operational radar performance. To achieve this, the miniradar dwell data must be scaled to take account of hardware differences between it and the operational radar. Some differences can never be accounted for in an exact way. For instance the miniradar receiver beam will be much broader than an operational radar’s and hence any fine azimuthal structure in the propagation conditions will be smoothed with the miniradar. Scaling o f miniradar cell powers to operational radar capability is another example. Weak clutter which lies below the noise level o f the miniradar system may be detected with the more sensitive operational system. The precise behaviour of this clutter in the Doppler domain is not known and must be estimated using extrapolation. There is no easy way around these miniradar limitations. The degree to which the miniradar can provide good advice is ulti- mately limited by the degree to which these limitations impact. The scaling problem may be broken into two major steps. The first involves sorting the dwell image into clutter and background noise, and scaling each independently. The second considers the extrapolation of the scaled clutter to the scaled noise floor.

The sorting algorithm receives the estimated level of the background in each miniradar dwell from the clean-up process. It is important that the miniradar be externally noise limited (i.e. external noise >> internal noise), so that the environmental conditions are meas-

IEE Proc-Radar, Sonar Navig., Vol. 143, No I , Febehuuary 1996

ured as accurately as possible. A parameter which represents a threshold above the noise floor is also passed. The module then designates cell powers above this threshold as clutter and cell powers below it as background noise. A low value of this threshold is useful, in that more clutter information is retained; however the data also become less reliable. Of particular note is the problem of azimuth sidelobes. When the weak signals of sidelobes are permitted through as legitimate main beam clutter, they are scaled to operational radar sensitivity and may appear as useful layers. This is especially true of sidelobe-generated E, layers. By setting the threshold higher this problem is ameliorated.

The actual amount of scaling takes into account transmitter and receiver site differences. For similar propagation paths, the backscattered clutter power spectral density, P, (dBW/Doppler cell), contained in a radar range-Doppler cell is related to the correspond- ing miniradar range-Doppler cell power density, Pm, by

where P,' is the radar transmitter power P,' is the miniradar transmitter power G,' is the radar transmitter antenna gain G,' is the miniradar transmitter antenna gain B,. is the radar waveform bandwidth B, is the miniradar waveform bandwidth 2, is the miniradar coherent integration time z, is the radar coherent integration time A is the additional gain of the miniradar receiver path over and above the radar path before calibration signals are injected.

Note that the clutter has been treated as a continuum spectrally, so that it scales with different values of 7. This is not an entirely correct assumption as the sea and land spectra, although complicated with higher

order spectra, must really be discrete. As the detected spectrum is also convolved with effects in the ionosphere, the assumption of the continuum is more realis- tic, but at certain velocities (e.g. at the first-order Bragg lines ancl the land clutter) large corrections due to widely different values, of z would lead to erroneous predictions of SBR. Fortunately the area in velocity space which must be of most interest is usually in the higher order spectra clutter or in the noise where the assumption of scaling with z will be more accurate.

The background level in an externally noise-limited receiver system is determined by the ambient noise spectral density N , aind the effective receiver bandwidth. Ai1 assumption is made that the measured noise level is not affected by the radar transmitter. The effective specmil bandwidth in the dwell output is limited by the coherent integration time z in the signal domain. The background level also depends on the receiver differences ithat were described for the clutter. The effective scaled radar background level, p,, in units of dBW/ Doppler cell can be thus represented, in terms of the miniradar level, om, by

b=- im+(F) dB -a ( 2 )

Once the clutter and background levels are scaled, there remains a region of the Doppler spectrum between the weakest clutter powers detected with the miniradar and the scaled background level where no information exists. When observed with an operational radar, this region often contains weak clutter, the so- called cl utter 'skirts'. An extrapolation technique is required if the skirts are to be created using only the existing rniniradar profile.

The current extrapolation technique first works out the averaige slopes from the peaks to the edges of the existing clutter information, M(r) . This process is repeated for all range cells. The measured slopes are smoothed as a function of range cell using a running mean and then used in a power law to extrapolate down to the noise floor at each range. The power law extrapolation modifies the measured clutter slopes so

E 3000

6 2500 Y

L 2 2000 Q

$ 1500 rn

E a, 3000 1

cn $ 2500 a 7 2000 e (5, 1500

26'30km Deak -145dBW

25 0 - 25

2690 km peak - 136dBW outbound knots inbound

- 20

-40

- 60

- 20

-40 $

- 60

25 0 - 25 25 0 -25 outbound knots inbound outbound knots inbound

-195 -190 -185 -180 -175 -170 -165 -160 -155 -150 -145 clutter level, dBW1Doppler cell

Fig. 12 Raw miniradar power dwell (bottom lef?) und a dwell which hus been rcaled to the sensitivity of a typical operational OTHR and had the first-order Doppler &imate removed (top left) The corrected dwell hds the Bragg pedks centred very close to OHz WRF = 5 OHz, BW = 15klds, beam = 2, CIT = 25 6% range = 1000-3460km, frequency = 22 893MHz

IEE Pro< -Rudur Sonur Nuvig Vol 143 No I Fehiuu~j I996 61

that they are steeper at high powers, and gentler at low powers. The modified slope, Mmod, is a function of Doppler and range and is given by

Mm&(?",d) = 3p""(d)M(r) ( 3 ) where the power index is estimated by

pow(d) = ( (Pm(d) - ( P T + 45))/60 + 0.4) (4) This extrapolation was derived empirically and is designed to represent the average behaviour of the clutter skirts when scaled to operational parameters. An example of the effect of the extrapolation when scaled to the values of a typical operational OTHR, is shown in Fig. 12. It is envisaged that an extrapolation technique which is physically based would improve this module. This extrapolation is concerned with modelling ocean or land clutter. Typical forms of this clutter are reasonably well understood (S.J. Anderson, private communication), even if predicting them is still diff- cult.

8.2 Doppler shift removal The path of transmitted radiation with sky wave radar necessarily passes through the ionosphere. This is true for both ocean backscatter and reflections from targets. As a consequence, any Doppler shifts which are the result of ionospherically induced phase path variations, are added to the observed reflector Doppler shift. In general, the ionosphere imposes several phase path effects on a traversing radio wave. In addition to the first-order Doppler shift there is often a smearing of the Doppler spectrum due to weaker secondary paths PI.

One of the features of ASMA is the ability to provide relevant advice for ships of different speeds. With- out removing the ionospherically imposed Doppler shift it is incorrect to equate the Doppler space in the miniradar dwell-to-target speed. Once the first-order ionospheric Doppler shift is removed the dwell Doppler space can be transformed into target velocity, v, space through

x 2

where h is the radio wavelength and higher order Dop- pler effects have been ignored.

Removal of the first-order Doppler shift (from now on simply called the Doppler shift) has proved difficult. This is due to the variable nature of the clutter in the miniradar images. As well as the phase path variations alluded to above, the effects of strong multipath and path boundaries [7, 91 further confuse the issue. The current technique begins with an accentuation of the Bragg lines by a simple smoothing process. The Bragg lines tend to be aligned with constant Doppler, and so the smoothing is performed along the range axis.

To reduce the processing time, the algorithm deter- mines ranges where no clutter exists and marks these so that they are omitted from any further processing, This step is then followed by an attempt to determine the path boundaries in the image, because the Doppler shift can change quite abruptly at these points. A path boundary is a range where the signal changes from one ionospheric path, say E-E path, to another, say F-F. The mode boundary is detected by abrupt changes in the signal strength that are usually associated with it. Sometimes the paths are overlapped, resulting in the so-called multipath or multimode problem. In this case,

(5) 2) = --fj

62

the two paths will generally have two different Doppler shifts and the task of identifying a Doppler shift is ill- defined. In this case, the more powerful mode is likely to more strongly influence the Doppler estimate; however no special treatment for multipath signal is included in the algorithm.

Once the separate path boundaries are determined, the Doppler shift detection can begin for each path separately. As a first estimate the maximum in the clutter at each range cell is a good place to start. It will generally represent land backscatter or either of the two first-order Bragg bacltscatter returns from the ocean surface. If the maximum is the land return it represents the position of zero target velocity and the Doppler shift has been correctly measured. While if the maximum is one of the Bragg peaks then the velocity of these, V b , can be deduced from the equation for deep-water ocean waves,

where, g, is the gravitational acceleration at the earth's surface, and k is the water wavenumber.

The difficulty arises in deciding on which return, k Bragg or land, the measured peak represents. The line of Doppler estimate using the cell maxima tends to hop from land to sea as a function of range, depending on which line is dominant at that range.

The first attempt to overcome this made use of the known positions of the land masses in the surveillance area to decide on the expected landisea surface area ratio, and hence predict the ratio of the peak amplitudes. It ran into difficulties because of an inability to accurately convert from the radar measured group range to ground range. The problem was compounded with a difficulty in predicting the precise relative clutter amplitudes, which are related to the state of the sea, [lo], as well as the landhea ratio in the beam. Since the algorithm had no easy way of gaining a priori knowledge of the sea state another method was explored.

The method that is used in the present version of ASMA, performs a correlation between each Doppler spectrum and a Heaviside square function of width equal to three Bragg shifts. The correlation is first performed with the square function centred at the maximum power cell and then at one Bragg shift either side of the maximum. One of these three positions must be centred on the land clutter, i.e. the Doppler estimate that we are searching for. To proceed, the maximum of the correlations is chosen as the new estimate of the Doppler shift. The assumption is that the correlation should be a maximum when the square function is centred on the land clutter, because in that case the land and the the two first-order signals should be included in the sum. This assumption can break down if there is multipath data, or strong Doppler smearing on one of the first-order Bragg signals.

Once the correlation is performed on the entire dwell the Doppler estimate generally has regions in range where the estimate is correct, but has other regions where the Doppler estimate is in error by precisely one or two Bragg shifts. Often these regions are small, and appear as small faults on an otherwise good estimate. A means of filtering the errors is the sigma filter which replaces datum points that fall too far outside an average value of neighbouring points, by a datum point that equals the average of the neighbouring points after

IEE Proc -Radar, Sonav Navig , Vol 143, No I, February 1996

filtering. The final step is to smooth the latest estimate as a function of range. Once again the smoothing does not cross path propagation boundaries. An illustration of the final estimate is shown in Fig. 12 along with the dwell with the Doppler estimate removed. Notice that the scaled Bragg lines are now constant in Doppler and that they are centred around OHz shift.

The removal of Doppler shift is the most problematic module in ASMA. It performs well in over 90% of dwells but this is barely adequate because of the very strong dependence of conditions on velocity, especially around the Bragg scatter. The task of Doppler shift removal is made more difficult if the miniradar WRF is set too high for the operating frequency and CIT, because the information is more narrowly confined in Doppler space and hence is more poorly resolved. At lower HF frequencies, it is important that a miniradar be able to transmit at a WRF as low as 2Hz (for a CIT of roughly 30 seconds) when collecting data for surface-mode advice.

8.3 Scaling to minimum detectable radar cross-section While the clutter power is a suggestive indicator of the ionospheric loss, the minimum detectable cross-section or MDRCS is more pertinent to radar operations. MDRCS is the minimum cross-section that a target can present to the radar and still be detected. In the context of surface mode the MDRCS must be treated as a function of target velocity because it has a strong dependence on this parameter. To determine the MDRCS as a function of range and velocity requires the knowledge of the size of the target which will appear in the radar dwell as a function of range. The signal level of the target at any range, Tr(v) is given by the radar equation:

where (7)

and P,' is the radar transmitter power G,' is the radar transmit antenna gain q,' is the radar transmit antenna efficiency and is equal to liL, L, is the transmitter system loss

is the effective backscatter cross-section of the target 1 is the one-way path loss (assumed to be the same for outward and return) R is the group range of the target G,' is the realised gain of the OTHR receiver array h is the wavelength of the transmission P, is a factor for polarisation mismatch at the receiver antenna 6 is receiver system gain between the antenna and the calibration point.

Many of these parameters only require knowledge of the hardware. We immediately see though that some knowledge of the propagation is required. The ionospheric loss is most crucial. The ionospheric loss can be determined by looking at the clutter at the range of interest. The clutter level for the radar, C,(v) can be

IEE Proc.-Radar, Sonar Navig.. Vol. 143, No. 1, February I Y Y 6

written as G; x2 c, = RT-P,6 4n

where P," Gf: qF 1 1

F, = ~- DoA- - 4x112 4nR2 l 2

(9)

and 0, is the ground backscatter coefficient; A is the ground scattering area and is given by

where &R is the range resolution attained with the radar; 6qi is the azimuthal resolution attained with the radar and q is the angle of incidence of the ray on the ground.

Combining eqns. 7 and 9 we get

If we include a nominal, threshold SBR for the tracking system of StdB, we can substitute StdB + Pb as the minimum detectable target strength where P , is the power of the background cell, and so,

MDRCS(r , d ) d ~ == ( Q , A ) ~ B + P ~ ( T , d ) d ~

+ ( & ) d B - C T ( T ) d B (13) Most of ithe information required to solve this equation can be extracted from {he scaled miniradar dwells. C,(r) can be obtained by summing the clutter across Doppler space, wlhile Pb(v, d, is simply the cell powers in the scaled dwell. S, is a function of the tracking system that is used. To complete the solution we require an estimate of the ground backscatter coefficient. This is unfortunately a rather difficult parameter to measure and can vary by 30dB or more depending on the state of the scattering medmm. As reliable, real-time estimates are not available as yet, it was decided to leave its calculation to a latter date and simply provide a stub value of -23dB. This value is often used for a fully developed ocean [I], although there is even uncertainty in this value. Work is progressing in providing better values of the coefficient in the future (S.J. Anderson private communication), and this architecture allows ease of installation when they arrive.

8.4 Scaling to SBR The MDRCS is a good indicator of the propagation conditions but does not absolutely measure how well the radar will detect a specific ship. While the conditions may be excellent for detecting an aircraft carrier they may be very poor for a patrol boat. To resolve this problem the ship cross-section of interest must be compared to the MDFICS to establish an excess SBR for that ship. Positive values of excess SBR mean that the ship 'should be detectable (and trackable on sensitivity grounds) while ,a negative value means that it won't. Ship Cross-section will generally be a function of frequency and so this step is also important for accurate frequency advice.

The difficulty in this exercise is in obtaining accurate cross-section data for ships. Some work is being done, but the large size of most ships means that modelling radar cross-sections is computationally expensive. Once again, because of the uncertainty in the development of these data, target cross-sections have been left as a stub which prompts the operator for a nominated scalar value.

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automated propagation advice for othr ship detection

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