Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third dimensionality recognition.In this paper,combined with the actual triple star orbits,a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis(PCA)is presented.Firstly,interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain.Secondly,as a method with simple principle and fast calculation,the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics.Finally,the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA.The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49%and random noise introduced by the receiver.Meanwhile,due to the influence of orbit distribution of the actual triple star orbits,the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results.This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

3D Target Localization Based on FrFT from Spaceborne Curve SAR

Synthetic aperture radar(SAR)three-dimensional(3D)imaging technology can reconstruct the complete structure of observed targets and has been a hot topic.Compared with tomographic SAR,array interferometric SAR,and circular SAR,curve SAR can use less data to achieve 3D positioning of targets.Most existing algorithms for estimating Doppler frequency modulation(FM)rate are based on sub aperture partitioning,resulting in low computational efficiency.To address this,this article establishes a target height estimation model,which reflects the relation-ship between the height and the residual Doppler FM rate for spaceborne curve SAR.Then,a fast SAR 3D localization processing flow based on fractional Fourier transform(FrFT)is proposed.Experimental verification demonstrates that this method can estimate the Doppler FM of the target column by column,and the 3D position error for non-overlapping targets is controlled within 1 m.For overlapping points with an intensity ratio greater than 1.5,the root mean square error(RMSE)of the estimation results is around 5 m.If the separation between overlapping points is greater than 35 m,the RMSE decreases to approximately 2 m.

Ground moving target detection and location based on SAR images for distributed spaceborne SAR

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.

Application of the RPC model for spaceborne SAR image geometric processing

An increasing number of low,medium,and high resolution SAR satellites creates a demand for a generalized sensor model to replace the rigorous sensor model(RSM).The rational polynomial coefficient(RPC)model is a generic sensor model which accurately fits the object-image geometry for various sensor systems with different coefficient values.It has been widely used as an alternative to RSM for photogrammetric processing of optical images,but its applications to SAR images are rarely discussed in publications.In this paper,the feasibility and practicability of the RPC model for SAR images are studied.The RPC model can not only be used to replace the RSM(range–Doppler model for SAR),but also applied to the processing chain for SAR data,thus facilitating the processing of SAR and InSAR data for end users.