Radar Target Detection Based on Waveform Design under Atmospheric Attenuation

Abstract

Under the condition of atmospheric attenuation, the mismatch of radar echo signals leads to the decrease of signal-to-noise ratio (SNR) and detection probability. A joint optimization algorithm for transmitting signal and receiving filter of MIMO radar with atmospheric system response is presented in this paper. Considering the energy constraint, similarity constraint and spectral coexistence constraint of the transmitting signal, and introducing the atmospheric channel response matrix, the echo model under the atmospheric response condition is constructed. By optimizing the transmitting signal and the receiving filter, the echo signal SNR and radar detection probability can be improved. On this basis, the ARMA stochastic model is used to simulate the atmospheric system response. Solve non-convex problems by matrix optimization, positive semi-definite relaxation, Charnes-Cooper transformation, and loop optimization methods. Finally, the rank-one matrix decomposition method is used to extract the optimal signal from the signal autocorrelation matrix. And we analyze the convergence of the algorithm, the degree of SNR improvement and the detection probability. Through numerical experiments, it is proved that after the atmospheric channel response is introduced and matched correctly, the SNR of the echo signal can be improved and the radar detection probability can be greatly increased.