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.

Airborne bistatic radar faces two main challenges when operating in look-down mode. One challenge is the issue of range cell migration (RCM) and Doppler migration (DM) due to movement between target and radar, while another challenge is the non-stationary nature for clutter. For the sake of tackling these challenges, a combined approach using sub-aperture processing is given. The method involves compensating for clutter Doppler and implementing sliding window processing to achieve sub-aperture space-time processing and eliminate clutter. Subsequently, spatial-temporal filtering elements with consistent phase are combined and reorganized to create the reconstructed echo matrix. RCM correction and coherent integration within each sub-aperture are then achieved through aperture division. Finally, RCM/DM compensation is carried out across diverse sub-apertures to realize energy integration. The effectiveness for this methodology is confirmed through simulation and processing of measured data.

Under the large time-bandwidth product condition, the detection of hypersonic maneuvering target usually confronts two main issues: the scale effect (SE) and range migration (RM)/Doppler migration (DM). To address these issues, this paper considers the intrapulse and interpulse motions simultaneously to establish the echo model of hypersonic target with acceleration firstly. Then, the matched filtering-scaled modified location rotation transform (MF-SMLRT) method is proposed to jointly eliminate the SE and RM/DM, which are realized by searching target’s rotation angle , initial range cell and acceleration. The proposed method shows better pulse compression (PC), integration and detection performance than the conventional narrow-band long-time coherent integration (CI) methods and existed CI methods applicable to large time-bandwidth products (LTBP) condition. Finally, simulated results are given to certify the validity of the proposed method.

This article explores the coherent integration and parameter estimation problem for high-speed target detection using bistatic multiple-input multiple-output (MIMO) radar. Unlike the traditional intrachannel coherent integration that could only focus the target’s energy during the multipulse observation, the bistatic MIMO radar implements joint intrachannel integration and interchannel integration to improve detection performance. However, its difficulties lie in that the high-speed motion results in the range migration (RM) in the intrachannel and the phase and envelope differences among multichannel. To solve these problems, we propose a multichannel coherent integration methodology in the radon Fourier transform (RFT) domain for the bistatic MIMO radar. First, we apply the RFT to integrate the target energy in the intrachannel. Then, the multichannel coherent accumulation is performed by the design of the phase compensation function and envelope alignment function. Finally, based on the relationship between the integration peak’s location and target parameters, a Broyden-like method and linear equation solving are, respectively, presented to estimate the target’s position and velocity. The effectiveness of the proposed method is assessed via simulation experiments and real-measured data. It is further noted that the proposed method can detect targets at low signal-to-noise ratios (SNRs) which are not attainable using state-of-the-art methods.

Airborne radar mainly confronts two problems for marine moving target detection. One the one hand, the relative velocity and acceleration between airborne radar and target cause range cell migration (RCM) and Doppler frequency spread (DFS), degrading the CI performance. On the other hand, heavy sea-clutter influences the focusing/detection results. To solve these problems, this paper proposes a novel fast method based on time slice location rotation transform (TSLRT), matched filtering processing (MFP) and singular value decomposition (SVD), i.e., TSLRT-MFP-SVD. This method combines the ideas of time slices division and echo subspace decomposition to realize valid CI and sea-clutter restrain. Real-data processing prove the validity of the proposed method.

In this paper, we present an algorithm for curvilinear Video-SAR (CViSAR) persistent imaging with distortion correction. Firstly, we derived the mapping between the actual and reconstructed location of any target in any frame image formed by curvilinear persistent polar format algorithm, named as curvilinear persistent mapping (CPM). Then, through a combination of the non-uniform input wavenumber spectrum with the non-uniform output imaging grids calculated by CPM, distortion-free frame images can be formed directly via a single non-uniform fast Fourier transform of type 3 (NuFFT-3). Simulation experiments are provided to demonstrate the effectiveness of the proposed algorithm.

For conventional polar format algorithm (PFA), because of the image distortion and defocus caused by the plane-wave assumption, the effective imaging scene is bounded to a small region near the reference point. In this paper, refocusing and zoom-in polar format algorithms (RZPFAs) for curvilinear spotlight synthetic aperture radar (SAR) imaging are proposed, which can produce refocused image for an arbitrary region of interest (ROI). First, refocusing is implemented by a phase compensation of the already dechirped signal with respect to the new refocusing point. The relation [named refocused distortion mapping (RDM)] between targets' actual locations and their reconstructed locations in the refocused image is then derived. Based on the RDM, the distortion-negligible region (DiR) and defocus-negligible region (DeR) are defined as extents within which the residual distortion and residual defocus are less than some preselected thresholds. When the ROI is within both the DiR and the DeR, zoom-in imaging based on nonuniform fast Fourier transform of type-1 (NuFFT-1) is sufficient to form a desired image, which is named RZPFA based on NuFFT-1 (RZPFA-1). However, when the ROI exceeds the DiR, zoom-in imaging based on nonuniform fast Fourier transform of type-3 (NuFFT-3) should be selected, which is named RZPFA based on NuFFT-3 (RZPFA-3). With just a small amount of extra computation than RZPFA-1, RZPFA-3 can realize pixel-based quasi-orthorectified imaging directly. Besides, the proposed algorithms can also be extended to wide-area persistent imaging where ROI is larger than DeR. The simulation and real data results demonstrate the effectiveness of the proposed algorithms.

This study addresses the coherent accumulation problem for detecting a manoeuvring target with complex motions, where range migration (RM) [i.e. range walk (RW) and range curvature (RC)] and Doppler frequency migration (DFM) occur during the coherent integration time. An efficient approach based on generalised keystone transform (GKT), radon transform (RT) and generalised dechirp process (GDP), i.e. GKT‐RT‐GDP, is presented to eliminate the RM and realise the coherent accumulation. More specifically, the GKT operation is first employed to remove the RC. Then, the RT is applied to estimate the trajectory slope for RW correction and velocity estimation. After that, GDP is introduced to obtain the estimations of target's acceleration and acceleration rate motion. Thereafter, the DFM caused by target's high‐order motions can be compensated and then the coherent integration can be realised via Fourier transform. The advantage of the presented algorithm is that it can obtain a good balance between the computation cost and the detection performance, in comparison with the existing coherent integration algorithms.

This letter considers the motion parameters estimation problem for a maneuvering target with arbitrary parameterized motion. The slant range of the target is modeled as a polynomial function in terms of its multiple motion parameters and a fast estimation method based on adjacent cross correlation function (ACCF) is proposed, where the iterative adjacent cross correlation operation is employed to remove the range migration and reduce the order of Doppler frequency migration. Then the motion parameters are estimated via Fourier transform. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can estimate the parameters without searching procedure and acquire close estimation performance at high signal-to-noise ratio (SNR) with a much lower computational cost. Finally, simulations are provided to demonstrate the effectiveness.

This letter considers the coherent integration problem for a maneuvering target, involving range migration (RM) and Doppler frequency migration (DFM) within one coherent pulse interval. A new coherent integration method, known as Radon-Lv's distribution (RLVD), is proposed. It can not only eliminate the RM effect via jointly searching in the target's motion parameters space, but also remove the DFM and achieve the coherent integration via Lv's distribution (LVD). Finally, several simulations are provided to demonstrate the effectiveness. The results show that for detection ability, the proposed method is superior to the moving target detection (MTD), Radon-Fourier transform (RFT), and Radon-fractional Fourier transform (RFRFT) under low signal-to-noise-ratio (SNR) environment.