Noise suppression method for multi-subband radar signal fusion

All-pole model constructs a linear model of signal, and various parameters of the estimated signal can be obtained by fixing the order of the model and calculating it, so as to realize signal prediction. Before sub-band fusion, coherence processing is required and can be solved by means of coherence function and so on. Since the root-MUSIC algorithm is not robust in pole selection in a low signal-noise ratio environment, it will cause the model to judge the order incorrectly. In order to solve the problem that the order estimation of subband fusion is inaccurate when the signal-to-noise ratio is low in the all-pole model, a noise suppression method was proposed. The main diagonal singular value matrix of Hankel matrix was weighted to eliminate the noise component, and the overall forward prediction matrix was used to obtain the pole value and pole amplitude of the multi-subband fusion signal, so that the multi-subband fusion signal at low signal-to-noise ratio was estimated. The results show that the proposed method has better estimation results than the traditional pole-model scheme when the signal-to-noise ratio is -20 dB to 10 dB in simulation environment.