This study focuses on the coherent integration (CI) of space-based distributed radar for space high-speed maneuvering targets. The platform space difference and high-speed motion result in the envelope position offset and phase difference of the inter-channel signals. Meanwhile, the high-speed and maneuvering characteristics of the target will lead to the range walk (RW) and doppler walk (DW) in the pulse accumulation in single node, which brings challenges to the detection of space targets. This paper presents a method for spatial-temporal joint coherent integration and parameter estimation based on the time-space range history. Firstly, based on the coupling relationship of spatial and temporal in the range history, we established inter-channel envelope correction and phase compensation function to address the inter-channel echo range and phase difference caused by spatial location differences between nodes. Secondly, we combined inter-channel synthetic compensation with generalized Radon-Fourier transform (GRFT). Thus, target range, angle, velocity, and acceleration parameter estimation are integrated into a unified framework. Finally, joint Spatial-temporal joint CI and parameter estimation for space-borne distributed radar system can be implemented. Simulation results demonstrate the effectiveness of the proposed method.
Reduced-dimension (RD) space-time adaptive processing (STAP) technique has achieved good clutter suppression performance in real data processing. However, the traditional F$A method suffers from performance degradation in presence of clutter fluctuation. Extended F$A method (E-F$A) is an effective approach to improve the performance in such a clutter environment, but it requires high computational complexity and sample support. In this paper, a novel reduced-dimension method for E-F$A clutter suppression is proposed. Firstly, we extract characteristics of clutter by tensor Tucker decomposition, which can preserve the structural characteristics of the clutter in the spatial and Doppler domains. Then, we select eigenvectors to construct the RD matrix based on principle components (PC) analysis. Finally, RD data is obtained by multiplying the RD matrix with the original data, and the weight vector for clutter suppression can be calculated. The experimental results based on real measured data validate the effectiveness of the proposed method.
For the long-range and high-speed maneuvering space target detection, its performance is constrained by two challenges, the coherent integration loss due to Range migration and Doppler frequency spread, the contradiction between Range Ambiguity, and Doppler bandwidth ambiguity. This paper proposed a novel parameter estimation and integration method to solve the above two issues. Firstly, the waveform diversity technique is used to solve the range ambiguity problem. Then a matched filter bank for high-speed targets that can calculate the range ambiguity number is designed. Next, coherent integration is successfully achieved by estimating the target motion parameters and compensating for the echo signal. Finally, a two-step search strategy is proposed to improve the parameter estimation process, numerical experiments have validated that the complexity of the algorithm is reduced while ensuring the accuracy of the parameter estimation.
Space-time adaptive processing (STAP) has been extended to the distributed space-borne multiple-input multiple-output (MIMO) radar system to improve the detection performance. Nevertheless, the transmitting waveforms are not completely orthogonal to each other, resulting in the STAP performance deterioration. In this paper, we established a novel STAP performance analysis model to reveal the influence mechanism of waveform properties. Firstly, the signal model of distributed space-borne radar with hybrid baseline and yaw angle was presented. Then, we derived the characteristic of the clutter covariance matrix for post-Doppler STAP, considering the effect of waveform periodic autocorrelation and cross-correlation sidelobe. Finally, the numerical simulation results, based on indicators of clutter eigenvalue spectrum and output signal-to-noise ratio loss, demonstrated the accuracy of the proposed analysis model. The aforementioned results provide important basis for the design of distributed space-borne MIMO radar system.
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