Clutter rejection is a key technique used by passive radars for target detection. Especially when using Single Frequency Network (SFN) configuration, the multipath clutter and ground clutter increase several times more than during a single illuminator situation, which means that the clutter extends in both the spatial and temporal dimensions. The high amount of clutter occupies numerous degrees of freedom when conventional spatial or temporal processing is used, leading to a large array requirement, a huge computational cost, or even a complete failure. This paper investigates a novel subcarrier-based processing technique that is tailored for Orthogonal Frequency Division Multiplex (OFDM) modulation with a Cyclic Prefix (CP-OFDM) to avoid the abovementioned predicament. The algorithm principle is initially illustrated and followed by a discussion about the unique characteristics of Subcarrier-based Spatial Adaptive Processing (SSAP), which include the Doppler response and its unusual main-lobe clutter case. Then, the robustness is researched by evaluating the performance under relaxed basic assumptions. The conclusions are demonstrated by conducting test using simulated and real data sets.

This paper focuses on the problem of the space-variance of the range-cell migration term for bistatic Synthetic Aperture Radar (SAR) and proposes a Scaled Inverse Fourier Transform (SIFT)-based imaging algorithm for the constant-offset configuration of bistatic SAR data processing. Range-cell migration correction is realized when two times phase multiplies and a convolution operation are executed. Because the imaging algorithm is based on a precise spectrum that has been deduced from the Geometry-Based Formula (GBF) algorithm, the proposed algorithm can handle the bistatic SAR data, which were obtained with a large baseline to ratio. The advantages and effectiveness of the proposed imaging method have been verified by simulated and comparable experiments. Moreover, unlike other scaling-imaging algorithms that are dependent on the frequency modulated characteristics of the signal, the SIFT imaging algorithm is also suitable for phase-coded signals, which are used in a wider range of applications.

This paper is proposed to eliminate the negative influence of the Rotational Phase Component (RPC) on the performance of the Doppler Centroid Tracking (DCT) phase compensation method. Firstly, the coherent property between adjacent echo pulses sampled directly in Intermediate Frequency (IF) is analyzed in the paper. Then a coherent phase compensation method is developed to improve the Translational Phase Component (TPC) estimation accuracy of DCT. Compared to the Modified DCT (MDCT) algorithm, the proposed method achieves better phase compensation performance. Experimental results prove the effectiveness and efficiency of the proposed strategy.

Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR) image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to
deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.

In this paper, an imaging processing method for Bistatic Synthetic Aperture Radar (BiSAR) utilizing navigation satellites is investigated. Considering the special problems regarding the use of Global Navigation Satellite System (GNSS) signals to form SAR images, direct signals are used to estimate range migration parameters, and range migration is corrected in the azimuth time domain. The Doppler sensitivity of phase-coded signals was solved by Doppler compensation. By fitting the Doppler phase history with a high-order polynomial, the Doppler phase history is accurately approximated and the azimuth compression is implemented by de-chirp processing. By performing simulations and experimental data processing, the proposed method is verified.

The active decoy jamming to SAR based on the Time-Delay Doppler-Shift (TDDS) method is effective in certain regions. Proper utilization of jamming to ensure good decoy quality requires a study of the effective region. After the mathematical analysis of the difference between the jamming signal and a real point-target echo, the paper points out that residual Range Cell Migration (RCM), matched filter error, and loss of Doppler bandwidth are three main factors that lead to a deterioration of the focus of a jamming signal. The formulation of the effective regions is obtained and verified by simulation results. The study indicates that the TDDS method can effectively protect limited regions around the jammer.

Geolocation is a very important step in Synthetic Aperture Radar (SAR) data processing. The precision of geolocation severely affects the applications of SAR images. This paper analyzes the influences on SAR geolocation caused by the traditional “stop-go” approximation, and establishes the range-Doppler equations for the real continuously moving configuration, and also provides a simplified way to solve the equations. Simulations and geolocation experiments on real SAR data of Beijing area validate the proposed method and show the correctness of the analysis.

Joint three-dimensional location algorithms aim to simultaneously obtain the north, east, and height coordinates of each pixel in several adjacent Interferometric Synthetic Aperture Radar (InSAR) scenes. Joint calibration is a key procedure used to achieve an accurate three-dimensional location. It can ensure the continuity of three-dimensional locations among adjacent scenes, and achieve the location of large areas with few Ground Control Points (GCPs) using Tie Points (TPs). In this paper, a new joint calibration algorithm for airborne interferometric SAR that simultaneously calibrates north, east, and height coordinates is proposed. It employs a weighted optimization method to carry out calibration, and introduces weights to calibration to discriminate GCPs and TPs with different coherences and locations. The experimental results for airborne InSAR data show that the three-dimensional location accuracy obtained using the proposed calibration algorithm is better than that obtained using the traditional method.

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.

We designed and implemented a wideband Linear Frequency Modulated (LFM) pulse compression exciter with 14.8 GHz carrier and 3.2 GHz bandwidth based on an ultra-high resolution airborne SAR system with a better than 0.1 m resolution. The selection of a signal generation scheme and some key technique points for wideband LFM waveform are presented in detail. Then, an acute test and analysis of the LFM signal are performed. The final airborne experiments demonstrate the validity of the LFM source, which is one of the subsystems in an ultra-high resolution airborne SAR system.

It is imperative to efficiently track and catalogue the extensive dense group of space objects for space surveillance. As the main instrument for Low Earth Orbit (LEO) space surveillance, ground-based radar systems are usually limited by their resolving power while tracking small, but very dense clusters of space debris. Thus, the information obtained regarding target detection and observation will be seriously compromised, making the traditional tracking method inefficient. Therefore, we conceived the concept of group tracking. The overall motional tendency of a group’s objects is particularly focused, while individual objects are in effect simultaneously tracked. The tracking procedure is based on the Bayesian framework. According to the restriction among the group center and observations of multi-targets, the reconstruction of the number of targets and estimation of individual trajectories can be greatly improved with respect to the accuracy and robustness in the case of high miss alarm. The Markov Chain Monte Carlo Particle (MCMC-Particle) algorithm is utilized to solve the Bayesian integral problem. Finally, the simulation of the tracking of group space objects is carried out to validate the efficiency of the proposed method.

In this paper, a new method of dual-threshold controlled adaptive clutter suppression is proposed for an airborne weather radar operated in the wind shear mode. To reliably estimate the center frequency and bandwidth of the clutter spectrum, the echo power in each range cell is used to design a dual-threshold controlled adaptive notch filter. This filter can reject the maximum amount of ground clutter, while reducing the effect of clutter residue on the wind shear signal. Results of our simulation have confirmed that this method has a superior clutter suppression performance, and can effectively improve the wind speed estimate accuracy of the wind shear signal.

As a new radar technology, the distributed aperture coherent radar is expected to be the next generation radar, which is easier to transport and less expensive than the traditional large aperture radar. However, the time synchronization and phase synchronization are key issues to be addressed for the distributed aperture coherent radar. In this paper, the error sources of time synchronization and phase synchronization are analyzed, and the
corresponding mathematical models are first derived. Then, the impact of synchronization errors on the coherent performance is simulated, and the accuracy of time and phase synchronization is presented based on the simulation results. Finally, the noncorrelation transmission scheme and the calibration scheme based on the wired transmission are proposed to realize the time and phase synchronization, respectively. Research of the
synchronization problem could be very helpful to realize the new radar technology of distributed aperture coherent radar.

This paper first reviews the history and trends in the development of spaceborne Synthetic Aperture Radar (SAR) satellite technology in the USA and Europe. The basic information regarding launched satellites and future satellite plans are introduced. Then, this paper summarizes and categorizes the imaging algorithms of spaceborn SAR satellites, and analyzes the advantages and disadvantages of each algorithm. Next, the scope and the application status of each algorithm are presented. Then, the paper presents details of trends related to the SAR imaging algorithm, which mainly introduces the algorithms based on compressive sensing theory and new image modes. The simulation results are also presented. Finally, we summarize the development direction of the spaceborne SAR imaging algorithm.

Micro-Doppler signature is one of the physical characteristics of the target. The radar signature of a target with micro-motion can make fine characterizations of the shape, structure, and moving state of target, which reflects the nonstationary property of a radar signal. Hence, it has great superiority in the analysis of sea clutter and target detection in the case of high sea states based on the micro-Doppler theory. In this paper, to show the need for micro-Doppler, the modeling of scattering clutter from time-varying sea surface and analysis methods of sea clutter Doppler are first reviewed based on the principles and characteristics of micro-Doppler. Then, applications and technological approaches of micro-Doppler in sea surface target detection are introduced from the perspective of micro-motion target modeling and detection methods of micro-motion signatures. Finally, future research interests are highlighted based on problems experienced in present studies.