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A Study on Automotive Anti-Collision Radars Based on Spread Spectrum Techniques By Anirudh Tadepally
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Outline Automotive Anti Collision Radars Different methods and proposals Method : Spread Spectrum Techniques Performance analysis Conclusion
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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
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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
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Possible Applications of AACR
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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
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Spreading Sequences Three types of sequences used: Gold Sequence: What is it? Characteristics Generators:
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Chaotic Sequences & Binary DeBruijn Sequences Chaotic Sequences: What is it? Characteristics Binary DeBruijn Sequences: What is it? Characteristics
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Autocorrelation of Binary De Bruijn sequence without peaks
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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)
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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
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Accuracy of the Radar Accuracy : Autocorrelation of considered sequence Cross correlation of whole set of sequences : Rejection (Interference) Simulation: Algorithm : applied to diff scenario
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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
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Performance Improvement Using Chaotic Sequences Maximizing correlation detection probability Minimizing false detection Probability Better Correlation Properties than Gold Sequences Better Range Resolution
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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.
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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
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