Noise Reduction in Automotive Pulse Radar using Signal Subspace and Presumed Ambiguity Function

Increasing demand for target detection accuracy under complex road conditions is a challenging issue for Intelligent Transport System (ITS). Weak target signals suffer heavily from heavy noise, especially at low signal-to-noise ratio (SNR). Therefore, effective noise reduction is crucial to enable better analysis of target signals. In pulse radar applications, the ambiguity function (AF) characterizes the time response of a filter matched to a given finite energy signal and resembles the form of a
$\rm {sinc}$
function for several types of transmitted signal waveforms. This paper addresses the problem of noise reduction for pulse radar with such waveforms. In particular, the pulse shape is designed in terms of the AF function. Furthermore, inspired by the fact that the signal subspace spanned by the received signals is dominated by the target echoes, a low-rank filter is developed to reduce noise for pulse echoes in the eigen-domain. Theoretical analysis and simulation results are both presented to demonstrate the improvement of SNR and detection probability.