Target tracking using particle filtering and CAZAC sequences

When tracking targets in radar, the selection of the transmitted waveform and the method of processing the return signal are two of the design aspects that affect measurement accuracy. Increased measurement accuracy results in enhanced tracking performance. In this paper, we apply sequential Monte Carlo methods to propose matched filtering operations in the delay-Doppler space where a target is expected to exist. Moreover, in the case of thresholding the measurements, these methods are used to form resolution cells that have the shape of the probability of detection contour. These methods offer an advantage over traditional radar tracking methods that form tessellating resolution cells to approximate the probability of detection contours, and exhaustively perform matched filtering operations over the entire delay-Doppler space. With the use of a Björck constant amplitude zero-autocorrelation (CAZAC) sequence, a high resolution measurement is attained and the use of thresholding is avoided. This is an advantage over commonly used waveforms such as linear frequency modulated chirps (LFMs). We examine the properties of Björck CAZACs and demonstrate improved tracking performance over LFMs in a single target tracking scenario.