Zhou-hao Pan

Compressed sensing application in interferometric synthetic aperture radar

A novel interferometric synthetic aperture radar (InSAR) signal processing method based on compressed sensing (CS) theory is investigated in this paper. InSAR image formation provides the scene reflectivity estimation along azimuth and range coordinates with the height information. While surveying the height information of the illuminated scene, the data volume enlarges. CS theory allows sparse sampling during the data acquisition, which can reduce the data volume and release the pressure on the record devices. InSAR system which configures two antennas to cancel the common backscatter random phase in each resolution element implies the sparse nature of the complex-valued InSAR image. The complex-valued image after conjugate multiplication that only a phase term proportional to the differential path delay is left becomes sparse in the transform domain. Sparse sampling such as M-sequence can be implemented during the data acquisition. CS theory can be introduced to the processing due to the sparsity and a link between raw data and interferometric complex-valued image can be built. By solving the CS inverse problem, the magnitude image and interferometric phase are generated at the same time. Results on both the simulated data and real data are presented. In comparison with the conventional SAR interferometry processing results, CS-based method shows the ability to keep the imaging quality with less data acquisition.

Side-looking 3D imaging of cross-track three-aperture synthetic aperture radar based on compressive sensing

Side-looking three-dimensional (3D) imaging of cross-track three-aperture sparse array synthetic aperture radar (SAR) based on compressive sensing (CS) is investigated in this paper. Conventional SAR has accomplished high resolution imaging on two-dimensional (2D) azimuth-range plane. Using the array structure in cross-track direction, the height resolution can be obtained and 3D imaging is achieved. Conventional imaging approach and imaging based on compressive sensing are used for imaging processing. The performance of both methods is analyzed. Numerical experiments have been made and simulation results are presented in this paper.

Airborne MMW InSAR interferometry based on time varying baseline and BP algorithm

Airborne interferometric synthetic aperture radar (InSAR) may exhibit highly non-linear flight paths, which cause the baseline to vary along the flight paths. In the following, a new airborne InSAR processing method which allows the baseline to vary along the flight paths is presented. It does not come to keep the assumption of a linear acquisition path and one constant interferometric baseline, which is adopted in conventional techniques. In addition, the validity of the proposed method was testified by both simulation and an example of its application.

Analysis and Compensation Method Research on the Channel Leakage Error for Three-baseline MMWInSAR: Analysis and Compensation Method Research on the Channel Leakage Error for Three-baseline MMWInSAR

Abstract: In this paper, modeling of the channel leakage error of a three-baseline MMWInSAR (MilliMeter Wave Interferometric Synthetic Aperture Radar) is analyzed, and the mathematical expression of the error’s parameters and interference phase error is deduced. Furthermore, using quantitative analysis, the paper investigates the impact on the interferometric phase error and elevation error from the channel leakage. Finally, a compensation method for the channel leakage error is presented. The results of simulation experiments verified the effectiveness of the compensation method.