Compared with the monostatic radar which only performs signal fusion in the multi-pulse dimension, the bistatic multiple-input multiple-output (MIMO) radar can also fuse multi-channel signals to improve the detection ability of high-speed moving targets. However, how to tackle the range migration (RM) caused by high-speed motion and compensate the signal difference between channels are the key problems in bistatic MIMO radar. To solve these problems, this paper proposes a computationally efficient multi-channel multi-pulse fusion algorithm. Firstly, we establish the echo model of bistatic MIMO radar with high-speed moving targets and utilize the Radon Fourier transform (RFT) algorithm to overcome the RM and complete the multi-pulse fusion. Then, the output characteristics of RFT, including peak and phase differences, are analyzed in detail. On this basis, a multi-channel coherent fusion method based on geometric information is proposed, which can eliminate the phase differences among channels and complete coherent fusion. Finally, numerical experiments show that the proposed algorithm can effectively detect the target under a low signal-to-noise ratio (SNR). Compared with the existing methods, the proposed algorithm can achieve a balance between computational complexity and detection performance.

The traditional two-step localization method for transmitter requires to estimate the signal parameters such as angle of arrival (AOA) and time of arrival (TOA), wich confronts the problem of localization error cumulation. While the direct position determination (DPD) can effectively reduce the estimation error and achieve superior localization performance than the two-step localization, which is widely applied in passive radar. Unfortunately, the uncertainty of the transmission signal parameters will causes the localization performance degradation for DPD method in passive localization. To address these issues, this paper considers the LFM signal transmitter localization with passive radar. Firstly, the signal within each receiving channel is accumulated by fractional Fourier transform (FrFT). Then the signal envelope alignment of each channel is performed in the FrFT domain by using the characteristics of FrFT, so as to realize the multi-channel signal accumulation. Finally, the transmitter is accurately localized by the two-dimensional position search. Simulation results show that the proposed method outperforms the two-step method and DPD method in low SNR.

When detecting high-speed targets, the strong spoofing of range deception interference (RDI) can lead to failure of true target detection. Fortunately, the fusion processing provides an effective solution to this problem. In this paper, the target echo model under RDI conditions is established based on the range history model for multistatic radar system. On this basis, we propose an effective RDI recognition and target detection method based on coherent fusion processing. Specifically, the method firstly realizes the coherent fusion of single-channel echo by Radon Fourier transform (RFT). Then, topology-based entropy circulation matching (TECM) is used to accomplish the acquisition of the matching positions about target and RDI in different channels. Finally, the matching position is processed by elliptic positioning (EP) to realize the recognition of RDI and target. Simulation experiments verify the effectiveness of the method.

This article addresses the multi-channel integration detection issue of high-speed maneuvering weak targets in airborne coherent multi-input multi-output (MIMO) radar. Coherent MIMO radar can significantly improve the detection performance through joint intra-channel and multi-channel fusion processing. Nevertheless, the range migration (RM) and Doppler frequency migration (DFM) are resulted from highspeed motion, and the envelope and phase differences among multi-channels are challenging. To address these limitations, we propose a multi-channel integration approach in generalized Radon-Fourier transform (GRFT) domain. First, the system and signal models are established. GRFT is utilized to accumulate intra-channel energy. Then, we construct a set of coupled equations, and estimate the target’s position, speed and acceleration with the Newton-Raphson algorithm and solving linear equations. Based on the estimated outputs, the envelope alignment and phase compensation functions are constructed to eliminate the differences across channels. After that, the multi-channel fusion is realized in GRFT domain. The superiority of the proposed approach is shown via simulations.