Daojing Li

Three-aperture inverse synthetic aperture radar moving targets imaging processing based on compressive sensing

Inverse synthetic aperture radar (ISAR) moving targets imaging processing is discussed in this paper. Due to the sparsity of the scene, the theory of Compressive Sensing (CS) is introduced to improve the imaging quality. Thus, super-resolution imaging is achieved. Combining real aperture with synthetic aperture, a hybrid model of imaging is proposed which allows imaging on a short radar coherent processing interval (CPI). A complex-valued image compression approach is proposed. Using two or more antennas, the random phase of image pixel can be eliminated and the frequency spectrum is sparse. Hence, the ISAR complex-valued image compression and reconstruction can be completed.

Simulation of signal reconstruction based sparse flight downward-looking 3D imaging SAR

Aimed at continuous scene imaging, this paper utilizes signal reconstruction method to eliminate random phases of scatter cells and reduce signal bandwidth, to achieve downward-looking 3D imaging in the condition of sparse flight for array SAR. With the sampling method of repeat flight such as 7 dense flights and 4 sparse flights with sampling criteria of [1 1 1 0 0 1 0] (Barker code sequence), [0 1 1 0 1 0 1] and [1 0 1 0 1 0 1] (uniformly-spaced sequence), respectively, the 3D imaging simulation is implemented in this paper. In addition, we compare the imaging quality before and after signal reconstruction. Simulation results illustrate that the adoption of signal reconstruction can significantly improve image quality; the combination of Barker code sparse flight and signal reconstruction presents the best performance among all the implemented methods.

Sparsity analysis of SAR signal and three-dimensional imaging of sparse array SAR

This paper analyses the sparsity of SAR signal under the multi-antenna observation structure. Based on the sparsity of continuous scene spectrum and sparsity of target scene, a down-sampling method is proposed and side-looking 3D imaging of cross-track sparse array SAR is investigated. Imaging results on simulation and real data are given to verify the proposed method.

Sparse Flight Array SAR Downward-Looking 3-D Imaging Based on Compressed Sensing

In this letter, we combine the airborne cross-track array synthetic aperture radar (SAR) technique and the sparse flight sampling method with a criterion of Barker code to generate a high-resolution downward-looking 3-D image. Furthermore, we propose an effective image reconstruction algorithm that is able to obtain image quality even with sparse sampling. Exploiting interferometry makes the SAR image sparsely represented in frequency domain, which can be naturally reconstructed with compressed sensing (CS) theory with sufficient precision and quality. The results of the simulation and experimental data of the anechoic chamber are presented, demonstrating the effectiveness of the algorithm.

Microwave three-dimensional imaging under sparse sampling based on MURA code

This paper utilizes Modified Uniformly Redundant Arrays (MURA) code as the criterion to realize sparse sampling in aperture plane, for the purpose of reducing bearing data storage. A geometry of microwave three-dimensional (3D) imaging is modeled, and the combination of ωK algorithm and Median Filter (MF) is adopted to achieve 3D image in the condition of sparse sampling. In addition, the imaging reconstruction based on Compressed Sensing (CS) and spatial sparsity is evaluated to make comparision. Numerical simulation and error analysis demonstrate the validity of proposed 3D imaging methods.

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.

A Reconfigurable, Scalable and Multifunctional Experimental AutoSAR and Its Applications

The concept of AutoSAR (automobile-based SAR) was first presented by Korean researchers. This kind of SAR systems can be installed on ground-based platforms, such as automobiles, trucks or trains, and has several potential advantages compared with space and airborne SAR system. In this paper, a reconfigurable, scalable and multifunctional experiments SAR system based on commercial instruments with its architecture, key factors in design and implementation, its applications and potential advantages is subscribed.

Interferometric inverse synthetic aperture ladar target detection method

To improve the target detection performance of inverse synthetic aperture ladar (ISAL) under the situation that there is Doppler bandwidth ambiguity, we consider energy accumulation of echo signals along a range through matched illumination. However, since the target impulse responses change with the target aspect angle, the phase shifts along slow-time between range cells are different, and the output of matched illumination fluctuates along slow-time. To reduce the slow-time fluctuation of matched illumination under additive white Gaussian noise assumption, we have proposed an interferometric ISAL (InISAL) target detection method based on interferometry processing and principal component analysis (PCA) in this paper. After the interferometry processing, the interferometric phase shifts along slow-time of all range cells are approximately the same. Then PCA is introduced to reduce the impact of noise, interference, and cross-terms of interferometry processing. Thus, the slow-time fluctuation of matched illumination can be decreased, and the target detection performance is improved. The proposed method has been validated with both simulated data of InISAL and real data of millimeter-wave interferometric synthetic aperture radar.

Vibration estimation of synthetic aperture lidar based on division of inner view field by two detectors along track

The wavelength of synthetic aperture lidar (SAL) is very short; vibration of millimeter magnitude will significantly change the phase of echo signal and lead to the defocus of imaging in azimuth direction, so vibration estimation is a key step of SAL imaging. The existing Space Correlation Algorithm (SCA) used to estimate vibration of SAL is only suitable for the condition of narrow azimuth beam and high signal-noise ratio (SNR). Based on division of inner view field by two detectors along track, a new data obtaining model of SAL is established in this paper. Furthermore, a new vibration estimation method is proposed. Simulations validate that the vibration of SAL can be accurately estimated in the condition of wide azimuth beam and low SNR with the proposed method, meanwhile, good imaging result is obtained.