Xueming Peng

Convolution Back-Projection Imaging Algorithm for Downward-Looking Sparse Linear Array Three Dimensional Synthetic Aperture Radar

General side-looking synthetic aperture radar (SAR) cannot obtain scattering information about the observed scenes which are constrained by lay over and shading efiects. Downward-looking sparse linear array three-dimensional SAR (DLSLA 3D SAR) can be placed on small and mobile platform, allows for the acquisition of full 3D microwave images and overcomes the restrictions of shading and lay over efiects in side-looking SAR. DLSLA 3D SAR can be developed for various applications, such as city planning, environmental monitoring, Digital Elevation Model (DEM) generation, disaster relief, surveillance and reconnaissance, etc. In this paper, we give the imaging geometry and dechirp echo signal model of DLSLA 3D SAR. The sparse linear array is composed of multiple transmitting and receiving array elements placed sparsely along cross-track dimension. The radar works on time-divided transmitting-receiving mode. Particularly, the platform motion impact on the echo signal during the time-divided transmitting-receiving procedure is considered. Then we analyse the wave propagation, along-track and cross-track dimensional echo signal bandwidth before and after dechrip processing. In the following we extend the projection-slice theorem which is widely used in computerized axial tomography (CAT) to DLSLA 3D SAR imaging. In consideration of the ∞ying platform motion compensation during time- divided transmitting-receiving procedure and parallel implementation on multi-core CPU or Graphics processing units (GPU) processor, the convolution back-projection (CBP) imaging algorithm is proposed for DLSLA 3D SAR image reconstruction. At last, the focusing capabilities

Polar Format Imaging Algorithm With Wave-Front Curvature Phase Error Compensation for Airborne DLSLA Three-Dimensional SAR

Airborne downward-looking sparse linear array 3-D synthetic aperture radar operates nadir observation and obtains the 3-D microwave scatter information of the observed scene. A polar format algorithm (PFA) with space-variant wave-front curvature phase error compensation is presented. A 3-D image in polar coordinate can be obtained with the proposed PFA, and a 3-D image in Cartesian coordinate can be obtained with interpolation. The proposed PFA possesses the advantages of high precision, low memory requirement, and low computational complexity. The focus performance of the proposed PFA is validated by 3-D distributed scene simulation with an airborne X-band digital elevation model and a P-band circular SAR image of the same area as simulation scene input.

Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

The airborne downward looking sparse linear array three dimensional synthetic aperture radar (DLSLA 3-D SAR) operates nadir observation with the along-track synthetic aperture formulated by platform movement and the cross-track synthetic aperture formulated by physical sparse linear array. Considering the lack of DLSLA 3-D SAR data in the current preliminary study stage, it is very important and essential to develop DLSLA 3-D SAR simulation (echo generation simulation and image reconstruction simulation, including point targets simulation and 3-D distributed scene simulation). In this paper, DLSLA 3-D SAR imaging geometry, the echo signal model and the heterogeneous parallel technique are discussed first. Then, heterogeneous parallel echo generation simulation with time domain correlation and the frequency domain correlation method is described. In the following, heterogeneous parallel image reconstruction simulation with two imaging algorithms, e.g., 3-D polar format algorithm, polar formatting and L1 regularization algorithm is discussed. Finally, the point targets and the 3-D distributed scene simulation are demonstrated to validate the effectiveness and performance of our proposed heterogeneous parallel simulation technique. The 3-D distributed scene employs airborne X-band DEM and P-band Circular SAR image of the same area as simulation scene input.

Autonomous Navigation Airborne Forward-Looking SAR High Precision Imaging with Combination of Pseudo-Polar Formatting and Overlapped Sub-Aperture Algorithm

Autonomous navigation airborne forward-looking synthetic aperture radar (SAR) observes the anterior inferior wide area with a short cross-track dimensional linear array as azimuth aperture. This is an application scenario that is drastically different from that of side-looking space-borne or air-borne SAR systems, which acquires azimuth synthetic aperture with along-track dimension platform movement. High precision imaging with a combination of pseudo-polar formatting and overlapped sub-aperture algorithm for autonomous navigation airborne forward-looking SAR imaging is presented. With the suggested imaging method, range dimensional imaging is operated with wide band signal compression. Then, 2D pseudo-polar formatting is operated. In the following, azimuth synthetic aperture is divided into several overlapped sub-apertures. Intra sub-aperture IFFT (Inverse Fast Fourier Transform), wave front curvature phase error compensation, and inter sub-aperture IFFT are operated sequentially to finish azimuth high precision imaging. The main advantage of the proposed algorithm is its extremely high precision and low memory cost. The effectiveness and performance of the proposed algorithm are demonstrated with outdoor GBSAR (Ground Based Synthetic Aperture Radar) experiments, which possesses the same imaging geometry as the airborne forward-looking SAR (short azimuth aperture, wide azimuth swath). The profile response of the trihedral angle reflectors, placed in the imaging scene, reconstructed with the proposed imaging algorithm and back projection algorithm are compared and analyzed.

Holographic SAR Tomography Image Reconstruction by Combination of Adaptive Imaging and Sparse Bayesian Inference

In this letter, we propose an imaging algorithm for the holographic synthetic aperture radar tomography in the circumstance of sparse and nonuniform elevation circular passes. Considering the anisotropic behavior of scatterers and the off-grid effect of sparse signal recovery, the algorithm combines the 2-D adaptive imaging method for circular SAR and the sparse Bayesian inference-based method for elevation reconstruction. For each circular pass, the azimuth-range 2-D image can be formed by the adaptive imaging method, which depends on the preretrieved maximum azimuth response angle and the azimuth persistence width. To deal with the off-grid effect in elevation reconstruction, which is caused by the deviation between the true scatterers and the discretized imaging grids, the off-grid sparse Bayesian inference method jointly estimates the scatterers and elevation off-grid error by applying their hierarchical priors. Compared with the conventional compressive sensing method that does not concern the off-grid effect, the proposed algorithm can provide more accurate 3-D reconstruction for pointlike targets, which is verified by the real-data experiments.

Modulating multicarriers with chirp for MIMO-SAR waveform diversity design

In multiple-input multiple-output synthetic aperture radar (MIMO-SAR), the orthogonal waveform diversity design plays a critical role. In this paper, we design multiple orthogonal waveforms by applying the multiple subcarrier technique in digital communications to commonly-used chirp radar waveform with large time-bandwidth product and constant modulus, so that the orthogonality of subcarriers within a common frequency band and good properties of chirp waveform are sufficiently exploited. The detailed modulation and demodulation methods are presented and the application potentials of the new waveform in MIMO-SAR are investigated. The proposed waveform diversity design method has the advantages of implementation simplicity and easy integration with the conventional SAR processor. Semi-physical simulation with an Agilent arbitrary waveform generator (AWG) and a high-speed oscilloscope (OSC) verifies the scheme. The performance is also evaluated by theoretical analysis and simulation results.