A Study on Automotive Anti-Collision Radars

Based on Spread Spectrum Techniques

By Anirudh Tadepally

Outline

Automotive Anti Collision Radars

Different methods and proposals

Method : Spread Spectrum Techniques

Performance analysis

Conclusion

Automotive Anti Collision Radars

What it does ?

Its Working: permit an automatic vision, Sends signals, Round-trip times help estimate the distance

Problems Encountered

Problems in multi user road : Interferences.

Correspondence of signals from the received echo

Design of a general AACR

Rules to be followed:

Frequency allocation: Spectral Occupancy

Allowable Power

Types:

Short Range Radars

Long Range Radars

Often used: LRR

Possible Applications of AACR

The technique in LRR: FM-CW systems

FM-CW systems capable of distance and speed measurement

Known frequency is modulated over a fixed period of time

Frequency difference b/w receive signal and transmit signal increases with delay.

Disadvantages

Interference of same type neighboring radars

Spreading Sequences

Three types of sequences used:

Gold Sequence: What is it?

Characteristics

Generators:

Chaotic Sequences & Binary DeBruijn Sequences

Chaotic Sequences: What is it?

Characteristics

Binary DeBruijn Sequences: What is it?

Characteristics

Autocorrelation of Binary De Bruijn sequence without peaks

DS SS Chaotic Radar: Analysis and Simulation

Radar Basics

Range to the Target :

R = cTr/2

Maximum Unambiguous Range:

Chip Duration: Tc = T/N

Range Resolution : ΔR = c . Tc/2

Radar Equation: Power density at range R from Isotropic Antenna = Pt/4ρR^2

Power Density at Range R from directive antenna = Pt . G/4ρR^2

Received Signal Power Pr: Pr = Pt G AS/((4ρ)^2 R^2)

Detection Algorithm for a multi-user Radar Environment

What is it?

How does it work?

Example: The following figure is an example of multiple targets in the radar operating range

Accuracy of the Radar

Accuracy :

Autocorrelation of considered sequence

Cross correlation of whole set of sequences : Rejection (Interference)

Simulation:

Algorithm : applied to diff scenario

Road Scenario & Factors Affecting

Road Scenario : Figure in the previous slide

Lane 3 (colored/ filled vehicle): Radar under Test

Lane 2 (Dashed vehicle) : Interfering Radar

No radars in other vehicles.

Result of Simulation shows:

interference signal of radar in lane 2 & multipath

signal due to useful radar : degrade our radar capability.

Signal Separation

Correlation properties

Performance Improvement Using Chaotic Sequences

Maximizing correlation detection probability

Minimizing false detection Probability

Better Correlation Properties than Gold Sequences

Better Range Resolution

Conclusion

Through the adoption of spread spectrum radars, based on direct sequence techniques, separation of the radar signals in a road multi-user environment may be solved.

The performance of such a kind of technique is strongly related to the correlation properties of sequence introduced in the spreading process, by evaluating the properties of different sequences, a suitable algorithm can be employed for better performances.

Chaotic Sequences adoption into the Radars provides better improvement than Gold Sequences.

References:

IEEE paper: "A Proposal of Automotive Anti-collision Radars Based on Spread Spectrum Techniques "By Ennio GAMBI, Franco CHIARALUCE, Giorgia RIGHI and Susanna SPINSANTE, Member, IEEE UniversitàPolitecnica delle Marche, DEIT - Via Brecce Bianche, 12 – Ancona - ITALY 1

ETSI EN 301 091-1: "Electro Magnetic Compatibility and Radio Spectrum Matters (ERM); Road Transport and Traffic Telematics (RTTT); Technical characteristics and test methods for radar equipment operating in the 76 GHz to 77 GHz band; Part 1: Technical characteristics and test methods

V. Venkatasubramanian, H. Leung, “A robust chaos radar for collision detection and vehicular ranging in intelligent transportation systems”, Proc. 2004 IEEE ITS Conference, Washington D.C., pp. 548-552.

Andrenacci S., Gambi E., Sacchi C., Spinsante S., “Application of de Bruijn sequences in automotive radar systems: Preliminary evaluations,” Proc. of 2010 IEEERadar Conference, 2010, pp. 959–964