vkandandan lec

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Signal Detection and Processing Techniques for Atmospheric Radars

Dr. V.K. Anandan

National MST Radar Facility

Department of Space

Gadanki - India

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• The essence of frequency analysis is the representation of a signal as superposition of sinusoidal components.

• In practical applications, where only a finite length of data is available, we cannot obtain a complete description of the adopted signal model.

• Therefore, an approximation (estimate) of the spectrum of the adopted signal model is computed.

The quality of the estimate depends on

How well the assumed signal model represents the data.

What values we assign to the unavailable signal samples.

Which spectrum estimation method we use.

• Clearly, a meaningful application of spectrum estimation to practical problems requires sufficient apriori information, understanding of the signal generation process, knowledge of theoretical concepts, and experience.

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Signal Detectability and Pulse Compression

• The efficiency of the radar system depends on how best it can identify the echoes in the presence of noise and unwanted clutter.

• The important parameters from the system point of view influence the radar returns are the average power of transmission and the antenna aperture size.

• Signal detectability is a measure of the radar performance in terms of transmission parameters.

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• Received signal power Psig to the uncertainty Pn in the estimate of the noise power

after averaging

Ae effective antenna area Pt peak power transmitted

pulse length, PRF pulse repetition frequency

Pave = PtPRF average Tx power Brec receiver band-width

Ts effective system noise temp. Nc No. of samples coherently added

Ninc number of resulting sums which are incoherently averaged

c 1/Bsig correlation time of the scattering medium for the wavelength used

t total integration time h range or height

h height resolution.

2112

21

21

2

/

/

/

))((

))((

sigavese

cc

recs

hte

inccrecs

sig

n

sig

BthPThA

tPRFBT

PA

NNBT

P

P

P

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• Average power is the important parameter for the strong returns and this is function of pulse length.

• Short pulses are required for good range resolution, and the shorter length of Inter pulse period (IPP) generates the problem of range ambiguity.

(Therefore maximum limit on the PRF is restricted due to the above problems)

• Pulse compression and frequency stepping are techniques which allow more of the transmitter average power capacity to be used without sacrificing range resolution.

• A pulse of power P and duration is in a certain sense converted into one of power nP and duration /n.

• In the frequency domain compression involves manipulating the phases of the different frequency components of the pulse.

• In the time domain a pulse can be compressed via phase coding, especially binary phase coding, a technique which is particularly amenable to digital processing techniques.

• Since frequency is just the time derivative of phase, either can be manipulated to produce compression.

• Phase coding has been used extensively in atmospheric radars and in commercial & military applications.

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Pulse compression

Barker codes• These were first discussed by

Barker (1953) and have been used in Ionospheric incoherent scatter measurements.

The distinguishing feature of these codes is that, the range side-lobes have a uniform amplitude of unity.

• The compression process only works, if the correlation time of the scattering medium is substantially longer than the full-uncompressed length of the transmitted pulse

+1

-1

+ + +

- -

+

-

Phase coded waveform .

Binary phase coded signal

14

ACF

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Complementary code pairs

• Barker codes have range side lobes which are small, but which may still cause problems in MST applications.

• Ideally a codes which supports high compression ratios (long codes) to get the possible altitude resolution.

• Complementary phase codes are binary in their simplest form and they usually come in pairs.

• They are coded exactly as Barker codes, by a matched filter whose impulse response is the time reverse of the pulse.

• The range side lobes of the resulting ACF output for each pulse will generally be larger for a barker code of comparable length.

• when the two pulses are complementary pair have the property that their side lobes are equal in magnitude but opposite in sign, so that when outputs are added the side lobes exactly cancel, leaving only the central peak.

+ + + - + + - + + + + - - - + -EDE2

ACF of pulse 1

16

8

+ + + - + + - + - - - + + + + - +ED1D

ACF of pulse 1

32

32

32

16

0

Sum of ACFs

16

8

-8

-8

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C(31) C(30) C(0)C(1)

Z-1 Z-1Output

Input

IMS A100 Modified transversal filter architecture

Decoding

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