Ground Moving Target Imaging Algorithm Research Articles

Clutter suppression and GMTI for hypersonic vehicle borne SAR system with MIMO antenna

This study proposes a clutter suppression approach and the corresponding ground moving target imaging algorithm for hypersonic vehicle (HSV) borne synthetic aperture radar (SAR) system with multiple-input-multiple-output (MIMO) antenna. HSV-borne radar platforms fly with a high speed, which can lead to severe Doppler ambiguity, and the radar system usually cannot provide enough channel freedom degree for clutter suppression. In this study, an SAR ground moving target indication (GMTI) approach with MIMO antenna is presented for HSV-borne radar. Compared with the traditional multichannel SAR GMTI methods, the proposed approach can provide more space freedom degree and obtain a wider imaging swath without decreasing pulse repetition frequency. Besides, the improved deramp space-time adaptive processing method decreases the ambiguity times of the ground clutter and focuses the moving target. The simulation results validate the effectiveness of the proposed method.

Clutter suppression and moving target imaging approach for multichannel hypersonic vehicle borne radar

In this paper, a clutter suppression and ground moving target imaging algorithm is proposed for the hypersonic vehicle (HSV) borne multichannel synthetic aperture radar (SAR) system. Different from the traditional horizontal flight radar platforms, the HSV-borne radar platform is with a complex movement, and typically has a skipping trajectory. Therefore, the clutter suppression and imaging operations are difficult to implement. To deal with this problem, a descending stage signal model of multichannel SAR system is presented and studied for the HSV-borne radar. Then, the clutter and moving target echoes are transformed into the azimuth frequency domain. Considering that there exists a phase difference between clutter and the moving target, the clutter suppression approach is implemented with a series of spatial domain filters. After that, the moving target is focused based on the keystone transform. In addition, the performance analyses and related issues of the proposed method are presented. Finally, some simulation experiments are taken to validate the effectiveness of the proposed method.

SAR Ground Moving Target Imaging Algorithm Based on Parametric and Dynamic Sparse Bayesian Learning

In this paper, a novel synthetic aperture radar (SAR) ground moving target imaging (GMTIm) algorithm is presented within a parametric and dynamic sparse Bayesian learning (SBL) framework. A new time–frequency representation, which is known as Lv's distribution (LVD), is employed on the moving targets to determine the parametric dictionary used in the SBL framework. To combat the inherent accuracy limitations of the LVD and extrinsic perturbation errors, a dynamical refinement process is further developed and incorporated into the SBL framework to obtain highly focused SAR image of multiple moving targets. An emerging inference technique, which is known as variational Bayesian expectation–maximization, is applied to achieve an efficient Bayesian inference for the focused SAR moving target image. A remarkable advantage of the proposed algorithm is to provide a fully posterior distribution (Bayesian inference) for the SAR moving target image, rather than a poor point estimate used in conventional methods. Because of utilizing high-order statistical information, the error propagation problem is desirably ameliorated in an iterative manner. The perturbations, known as the multiplicative phase error and additive clutter and noise, are both well adjusted for further improving the image quality. Experimental results by using simulated spotlight-SAR data and real Gotcha data have demonstrated the superiority of the proposed algorithm over other reported ones.

High-Resolution SAR Imaging of Ground Moving Targets Based on the Equivalent Range Equation

In this letter, a novel ground moving target imaging algorithm suitable for high-resolution synthetic aperture radar (SAR) is proposed. The key step of the proposed algorithm is to make a moving target equivalent to a static one based on the derived equivalent range equation. Due to such equivalence, the commonly used standard algorithms for stationary scene imaging (e.g., the range Doppler algorithm) can be easily adapted to focus moving targets by adding only a search operation. The proposed algorithm does not make any approximation to the range equation and is thus rather suitable for high-resolution imaging of moving targets. In addition, due to the used equivalence, to focus a slow-moving target with four unknown parameters (two motion parameters plus two position parameters), the dimensionality of the parameter search space is reduced to one. Experimental results of the simulated data validate the proposed algorithm.

Detection and Imaging of Ground Moving Targets With Real SAR Data

Detection and imaging of multiple moving targets is a challenging task, particularly with real synthetic aperture radar (SAR) data. In this paper, moving targets with different motion parameters are classified based on the relative locations of their spectra to that of the clutter. Based on the classification, a novel moving target processing strategy with real SAR data is proposed, including a two-step ground moving target indication (GMTI) algorithm and a practical ground moving target imaging (GMTIm) algorithm with motion error compensation. The two-step GMTI algorithm has the ability of indicating multiple moving targets, particularly those submerged by the clutter; the practical GMTIm algorithm shows a robust performance in real data moving target imaging since the motion errors are estimated and compensated. Both simulated and real data processing results are provided to demonstrate the effectiveness of the proposed strategy.

Ground moving target imaging algorithm for single channel airborne CSSAR

Airborne circular stripmap synthetic aperture radar (CSSAR) has the advantages of short revisit time and large coverage, and thus is an attractive tool for wide area surveillance. A novel ground moving target imaging algorithm for single channel airborne CSSAR is proposed. The proposed algorithm can be implemented without knowing a target’s motion parameters. Simulation results indicate that moving targets can be well focused by the proposed algorithm.