In modern high resolution SAR data, due to the intrinsic side-looking geometry of SAR sensors, layover and foreshortening issues inevitably arise, especially in dense urban areas. SAR tomography provides a new way of overcoming these problems by exploiting the back-scattering property for each pixel. However, traditional non-parametric spectral estimators, e.g. Truncated Singular Value Decomposition (TSVD), are limited by their poor elevation resolution, which is not comparable to the azimuth and slant-range resolution. In this paper, the Compressive Sensing (CS) approach using Basis Pursuit (BP) and TWo-step Iterative Shrinkage/Thresholding (TWIST) are introduced. Experimental studies with real spotlight-mode TerraSAR-X dataset are carried out using both BP and TWIST, to demonstrate the merits of compressive sensing approaches in terms of robustness, computational efficiency, and super-resolution capability.

CurviLinear SAR (CLSAR) is increasingly attracting considerable interest in the field of radar remote sensing. Various methods of 3-D target feature extraction and aperture design have been proposed, and these methods are classified in this paper. The basic theories of these methods are systematically studied and compared, and their advantages and disadvantages are summarized. Moreover, the main 3-D target feature extraction and aperture methods are described. Finally, the future research fields of CLSAR are proposed.

Multiple-Input Multiple-Output (MIMO) radar is an emerging radar system that is of great interest to military and academic organizations due to its advantages and extensive applications. The main purpose of Space-Time Adaptive Processing (STAP) is to suppress ground clutter and realize Ground Moving Target Indication (GMTI). Nowadays, STAP technology has been extended to MIMO radar systems, and MIMO radar STAP has quickly become a hot research topic in international radar fields. This paper provides a detailed description of the extension and significant meaning of MIMO-STAP, and gives an overview of the current research status of clutter modeling, analysis of clutter Degree Of Freedom (DOF), reduced-dimension (reduced-rank) processing, simultaneous suppression of clutter plus jamming, non-homogeneous environment processing, and so on. The future perspective for the development of MIMO-STAP technology is also discussed.

We investigate several important properties of an Adaptive Energy Detector (AED), which is originally proposed according to the Generalized Likelihood Ratio Test (GLRT), under the assumption that the signal steering vector is completely unknown. We show that the AED coincides with the Rao and Wald tests. We also give the exact statistical distribution, according to which one can easily derive the Probabilities of Detection (PD) and False Alarm (PFA), and we use the AED to design a parametrically tunable signal-mismatch detector. Compared to existing tunable detectors, the novel tunable detector is more flexible in governing the rejection of the mismatched signal; moreover, for the matched signal, the tunable detector can provide a higher PD than existing detectors. Two scalars, called the tunable parameters, control this functionality.

The Miniature Air Launched Decoy (MALD) flies cooperatively with a true target and construct unresolved targets within the radar beam. The unresolved targets and decoy result in echoes aliasing and observation merging, which causes serious measurement error and traditional track processing failure. Based on the analysis of jamming patterns and characteristics, the signal model of the unresolved targets is proposed. Combining jamming detection, echoes observation, and likelihood function characteristics, the proposed approach directly operates on the monopulse sum and difference returns and uses the particles propagating and evolving in the state space to obtain the conditional state probability density of the unresolved targets and decoy. This method effectively bypasses measurement extraction and parameter measurement, and realizes the joint tracking of the target and decoy. Furthermore, it provides the necessary conditions for target selection to the radar based on track and trajectory data. Simulation experiments illustrate the effectiveness of the proposed method.

A new method of Radar Cross Section (RCS) measurement based on near-field imaging of cylindrical scanning surface is proposed. The method is based on the core assumption that the target consists of ideal isotropic scattered centers. Three-dimensional radar scattered images are obtained by using the proposed method, and then to obtain the RCS of the target, the scattered far field is calculated by summing the fields generated by the equivalent scattered centers. Not only three dimensional radar reflectivity images but also the RCS of targets in certain three dimensional angle areas can be obtained. Compared with circular scanning that can only obtain twodimensional radar reflectivity images and RCS results in two-dimensional angle areas, cylindrical scanning can provide more information about the scattering properties of the targets. The method has strong practicability and its validity is verified by simulations.

Based on coherent accumulation matrix reconstruction, a novel Direction Of Arrival (DOA) estimation decorrelation method of coherent signals is proposed using a small sample. First, the Signal to Noise Ratio (SNR) is improved by performing coherent accumulation operation on an array of observed data. Then, according to the structure characteristics of the accumulated snapshot vector, the equivalent covariance matrix, whose rank is the same as the number of array elements, is constructed. The rank of this matrix is proved to be determined just by the number of incident signals, which realize the decorrelation of coherent signals. Compared with spatial smoothing method, the proposed method performs better by effectively avoiding aperture loss with high-resolution characteristics and low computational complexity. Simulation results demonstrate the efficiency of the proposed method.

The signal reconstruction algorithm with sub-Nyquist bandpass sampling in Pulse Position Modulation-Ultra Wide Band (PPM-UWB) signal processing is analyzed based on PPM-UWB signal demodulation. Then, the reconstruction method based on the annihilating filter and the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) algorithm are compared using simulations. The total least squares ESPRIT algorithm, which requires high bandwidth, has better anti-noise performance than the reconstruction method based on the annihilating filter.

In multipath environment, the conventional Capon beamformer suffers from signal cancellation mainly because of the variation in phase differences (near ±π ) between the array output corresponding to the signal of interest and multipath interferences. To solve this problem, a novel beamforming method for multipath signal reception is proposed. This method uses an antidiagonal unit matrix to construct a new covariance matrix and a constrained steering vector. Then, the weighting vector is obtained based on the minimum variance distortionless response criterion and the array output is performed. The proposed method does not have to estimate the direction of arrival of multipath interferences and uncorrelated interferences; moreover, the array output can improve by adjusting the number of array elements. The simulations demonstrate the superior performance of the proposed method over the conventional Capon and multipath signal reception methods.

A high-resolution real-time subaperture imaing formation for range direction pulse compression airborne strip Synthetic Aperture Radar(SAR) system is presented. It can be used in no dechirp strip SAR system. By pulse compression in range direction and Overlapped Subaperture Algorithm(OSA) in azimuth direction this algorithm can compensate the range-azimuth cross error and the space variant phase error. In this study, first strip SAR geometry is analyzed and the strip SAR model is derived, and then the processing flow of OSA for range pulse compression strip SAR system is described in detail. Computation load, data storage and limitations of patch are analyzed then.The point-target simulations and live data processing results show the proposed approach is feasible and effective.

Multiband SAR is an important trend in SAR technology. Accurate registration among different band SAR images is a prerequisite for the comprehensive utilization of the information of multiband SAR images. Errors in the motion measurement system (i.e., residual motion) are major error sources affecting image registration. To solve this problem, the effect of residual motion error on SAR imaging geometry positioning is investigated. The relation between residual motion and image registration accuracy of airborne multiband SAR is analyzed quantitatively. The results of the theoretical analysis are verified by simulation experiments.

The clutter characteristics of terahertz high-resolution radar are essential for terahertz radar detection. This study analyzes the traditional clutter probabilistic model and the corresponding parametric estimation methods. Terahertz high-resolution radar clutter measuring experiments are implemented, and the measured data are analyzed. The experimental results show that G0 distribution is the best technique to describe the clutter characteristics of the terahertz band.

This study uses time domain terahertz radar system to discuss systematic imaging studies on the scaled models based on the improved Back-Projection(BP) algorithm. We image the scaled models with different shapes and are able to distinguish spatial gaps as small as 6 mm. TheTheoretical calculation predicts that the lateral resolution and the axial resolution can be as high as 0.125 mm. Center enhancement and background rings caused by the algorithm in the imaging results are also qualitatively analyzed and are proposed methods to overcome this problem.

Video Synthetic Aperture Radar (ViSAR) system offers high imaging frame rate, and high resolution, and it is consequently used to investigate and locate near-moving targets. Compared with microwave SAR, the practical application of ViSAR is restricted by motion compensation caused by short wavelength. Even slight platform vibrations cause significant variations in the phase of echo signal.Thus, it is imperative to analyze the motion compensation and the error of ViSAR. In this study, the results show that imaging is affected less in the direction of flight direction and by low vibration in the direction of the slant range. In contrast, high-frequency vibration in the direction of the slant range requires higher compensation accuracy. Given the particularity of ViSAR's motion compensation, a compensation scheme is designed to achieve high compensation precision .The effectiveness of the scheme is verified by ViSAR imaging simulation experiments.