Wavelet Based Adaptive Detection of Automotive Radar Single Target with Low SNR
Alexandru Isar, Corina Naforniţa, Adrian Macaveiu, Georgiana Magu · 2020
We propose an adaptive detection algorithm combining two signal processing methods: ordered statistics and wavelet based denoising, with the purpose of detecting low SNR single automotive radar target. The detection is realized by denoising the Range-Doppler map obtained for the Rapid Chirps waveform, using a Hard-Thresholding filter applied in the wavelet domain. The threshold is selected as the maximum value of the medians of the Range-Doppler map resolution cells. We quantify by simulations the merits of each of the two signal processing methods used.