Cascaded Kalman filter for target tracking in automotive radar

Abstract

In automotive anti-collision radar system, the accuracy of velocity is one of the key indicators to measure radar performance. For frequency modulation continuous wave radar with chirp sequence, which is commonly used in automotive radar, there are two problems that are velocity ambiguity and measurement error. In order to address these problems, a cascaded Kalman filter algorithm is proposed in this article, which is able to overcome velocity ambiguity and improve the accuracy of measurements. In addition, the problem of velocity ambiguity can be solved just in the data processing and it avoids transmitting staggered or multiple pulse repetition frequency signal. The simulation results show that this algorithm can effectively improve the tracking performance.

Keywords

• Doppler radar
• measurement errors
• road vehicle radar
• Kalman filters
• FM radar
• CW radar
• target tracking
• frequency modulation
• radar signal processing
• target tracking
• automotive radar
• automotive anti-collision radar system
• key indicators
• radar performance
• frequency modulation continuous wave radar
• chirp sequence
• velocity ambiguity
• measurement error
• cascaded Kalman filter algorithm
• staggered pulse repetition frequency signal
• multiple pulse repetition frequency signal
• tracking performance