This paper investigates data processing approaches to detect and locate ground moving targets using distributed spaceborne SAR systems with long cross-track baselines. In particular, it investigates the performance of...This paper investigates data processing approaches to detect and locate ground moving targets using distributed spaceborne SAR systems with long cross-track baselines. In particular, it investigates the performance of ground moving target detection for two typical satellite formations： Cartwheel and Pendulum. An approach based on SAR images and a space-time adaptive processing （STAP） algorithm is proposed in order to overcome the effects of the ground terrain on the clutter suppression. The key idea of the approach is firstly to reduce the clutter degrees of freedom greatly by using conventional SAR imaging processing. Then the ground terrain clutter within each SAR pixel can be effectively cancelled by using the very limited spatial degrees of freedom. Finally, constant-false-alarm-rate （CFAR） techniques can be used to detect the remaining target SAR pixels after clutter cancellation. An approach to relocate the detected targets is also proposed, which is based on the estimation of the Doppler spectrum shifts of ground moving targets relative to the clutter Doppler spectrum. The proposed approaches in this paper have the advantages of simplicity and high efficiency.展开更多
The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covarian...The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.展开更多
文摘This paper investigates data processing approaches to detect and locate ground moving targets using distributed spaceborne SAR systems with long cross-track baselines. In particular, it investigates the performance of ground moving target detection for two typical satellite formations： Cartwheel and Pendulum. An approach based on SAR images and a space-time adaptive processing （STAP） algorithm is proposed in order to overcome the effects of the ground terrain on the clutter suppression. The key idea of the approach is firstly to reduce the clutter degrees of freedom greatly by using conventional SAR imaging processing. Then the ground terrain clutter within each SAR pixel can be effectively cancelled by using the very limited spatial degrees of freedom. Finally, constant-false-alarm-rate （CFAR） techniques can be used to detect the remaining target SAR pixels after clutter cancellation. An approach to relocate the detected targets is also proposed, which is based on the estimation of the Doppler spectrum shifts of ground moving targets relative to the clutter Doppler spectrum. The proposed approaches in this paper have the advantages of simplicity and high efficiency.
文摘The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.
