Abstract:Regarding the issue of detection equipment being within the range of spaceborne SAR sidelobe, which causes the signal to be lost in the strong noise background, a method based on data fusion between multi-platform receivers is proposed. Without knowing the signal form, the weak signals submerged in noise can be detected, and the signal can be classified and accurately estimated. Firstly, the reference receiver and other receivers are cross-correlated to obtain the peak information, and the delay position between the signals and the reference signal is obtained according to the position of the peak information, in order to perform delay calibration. Secondly, each receiver performs coarse step FrFT filtering, records peak information for precise estimation, and restores the original signal based on the peak angle and the inverse FrFT. Finally, it is determined whether there is a signal. If the signal is achieved, a new signal will be formed by the fusion of power ratio of multi-platform receivers' original signal. The rotation angle ranges are limited based on the peak information of multiple stations, and the precise step FrFT is used to estimate the chirp rate and central frequency. The joint cross-correlation spectrum analysis is used to realize the accumulation of signal energy, and the left and right boundaries in the signal persistence state are found by using the method of continuously minimizing the boundary valley. The bandwidth and central frequency are accurately estimated, and then calculate the pulse width. The simulation results show that this method can accurately estimate the parameters of the time-frequency domain of Chirp in the background of Gaussian white noise and colored noise with low noise.
