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 : "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 IEEE ITS Conference, Washington D.C., pp  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