Inverse Synthetic Aperture Radar System Research Articles

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application.

Time-Varying Reflectivity Modulation on Inverse Synthetic Aperture Radar Image Using Active Frequency Selective Surface

Interrupted-sampling repeater modulation (ISRM) can generate multiple virtual target images by sampling and forwarding radar signals to confront the inverse synthetic aperture radar (ISAR). However, the repeating delay is unavoidable and the system is complex. Moreover, numerous works mainly discuss the ISAR image deception based on periodic modulation, and the modulation effect is relatively limited. Active frequency selective surface (AFSS) can perform intermittent amplitude modulation to the reflected signal by varying target reflectivity, thus, it can achieve the function of ISRM. In this paper, the possibility of AFSS applied in the multiple virtual target generation is discussed, and an ISAR image-modulation method is proposed. The radar signal is periodically modulated by varying target reflectivity, which is accomplished by the AFSS-loaded PIN diodes. On this basis, the AFSS modulating frequency is randomly varied in a slow time domain. When the modulation signal is processed by the ISAR system, the produced target image is unfocused and cannot be recognized by radar. Simulation results are utilized to demonstrate the effectiveness of the proposed method.

Novel approach for shipborne‐passive bistatic imaging with DVB‐T signals based on MIAA–RID technique

The shipborne-passive bistatic inverse synthetic aperture radar system with digital video broadcasting terrestrial (DVB-T) signals is very important in the fields of radar imaging, but it suffers from the problems of grating lobes caused by the spectral gaps when multiple DVB-T channels are applied, and the non-stationary echo signal for the complex motions of the ship. In this paper, a new algorithm based on the Missing Data Iterative Adaptive Approach (MIAA) combined with the Range Instantaneous Doppler (RID) technique is proposed to address these problems. First, the authors establish the imaging geometry and signal model. Based on these models, the range resolution and Doppler frequency are analysed. Then, the bandwidth synthesis in the frequency domain for the DVB-T signal is derived. Finally, the MIAA method is used to recover the spectral gaps of the range profile for multiple DVB-T channels, and the azimuth compression is carried out by the RID method after the translational motion compensation. Simulation results show the effectiveness of the algorithm proposed in this paper.

Air Moving Target Imaging for Staggered ISAR

The rapid development of the modern electronic counter-countermeasures (ECCMs) has made the conventional inverse synthetic aperture radar (ISAR) associated with the regular signal waveforms more vulnerable and unreliable. To deal with this issue, the complex waveform designment with staggered pulse sampling is developed in an ISAR system in this letter. In the proposed method, the generalized time-scaled transform (GTST) is adopted to effectively accomplish the irregular signal reconstruction and linear phase decoupling. After that, a set of matched filtering functions are established and interspersed in the imaging processes to accomplish the subsequent motion compensation, target imaging, and range and cross-range scaling. Finally, a satisfied ISAR imagery corresponding to the real size of a moving target can be recovered. The simulation and real-measured radar data processing results are applied to demonstrate the effectiveness of the proposed method.

An Efficient Maritime Target Joint Detection and Imaging Method with Airborne ISAR System

In this paper, a joint maritime moving target detection and imaging approach, referred to as the fast inverse synthetic aperture radar (ISAR) imaging approach, based on the multi-resolution space−time adaptive processing (STAP), is proposed to improve the target detection performance and the target imaging efficiency in an airborne radar system. In the target detection stage, the sub-band STAP is introduced to improve the robustness of clutter suppression and to enhance the target output power with the decreased range resolution, by which the coarse estimation of target range-Doppler (R-D) location is obtained as the prior knowledge. In the following target imaging stage, the ISAR imaging is applied in the localized R-D zone surrounding with the target location. However, it is difficult to directly apply ISAR imaging with the conventional R-D algorithm because the slow-moving maritime target cannot be separated from the clutter interference in the Doppler frequency dimension. In this regard, the full-band STAP is applied in the R-D two-dimensional frequency domain for the simultaneous clutter suppression and high-resolution ISAR imaging, in which the envelope alignment and phase compensation are achieved by adaptive match filtering with the target Doppler frequency coarse estimation. Moreover, the reduced-dimension STAP applied in the target-surrounded localized Doppler frequency zone gives facilities for alleviating the computation burden. Simulation results corroborate the effectiveness of the proposed method.

Sparse aperture bistatic ISAR imaging under low signal-to-noise ratio condition

A sparse representation-based bistatic inverse synthetic aperture radar (ISAR) imaging method can achieve a high-resolution image of a target with sparse aperture data. However, the bistatic ISAR system is more sensitive to noise than the monostatic one because of its nonmirror reflection geometry. To overcome this drawback, we propose the sparse aperture bistatic ISAR imaging method based on joint sparse model. Considering the joint sparse information of bistatic ISAR echo, a joint sparse imaging model is constructed. Then, the dechirped sparse aperture bistatic ISAR echo after translational compensation is transformed into range fast time and azimuth slow time domains by the joint sparse imaging model, and a corresponding azimuth sparse basis is constructed. Then a joint sparse complex approximate message passing algorithm is proposed to joint sparse imaging model. The joint sparse imaging problem is converted to a block sparse imaging problem by vectorization. Using the relationship between the vectorization of the matrix and the Kronecker product, a matrix iteration structure is proposed to solve the joint sparse model efficiently and accurately. The experimental results based on both scattering point model and electromagnetic calculation model data verify the effectiveness of the proposed imaging method.

Imaging of target with complicated motion using ISAR system based on IPHAF-TVA

The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear.

FMCW ISAR Autofocus Imaging Algorithm for High-Speed Maneuvering Targets Based on Image Contrast-Based Autofocus and Phase Retrieval

From the perspective of radar signal processing, the pulse-Doppler radar signal model is mostly based on the stop-and-go model due to the short pulse propagation time. Unlike the pulse-Doppler radar, the frequency modulated continuous wave (FMCW) radar takes a long time in the process of signal transmission to echo reception. During this period, the target cannot be considered to be stationary during the acquisition of the entire sweep echo, so the stop-and-go assumption in the FMCW system is no longer valid, which means that the target's motion related to the fast time must be taken into account. In the inverse synthetic aperture radar (ISAR) imaging scenario of high-speed maneuvering targets, the frequency offset correction introduced by the target's motion becomes reasonably complicated that it is difficult to restore the usual ISAR signal processing. In this work, a new method based on phase retrieval and image contrast-based autofocus (ICBA) is proposed to address the complex problem of motion compensation for FMCW ISAR systems. To cope with the fast time-varying characteristics of the phase error and the higher number of phase terms relative to pulsed radars, the proposed algorithm performs fine compensation with higher accuracy, resulting in high-resolution and autofocus imaging. Experimental results demonstrate the effectiveness of the proposed method.

Dynamic Analysis of Spin Satellites Through the Quadratic Phase Estimation in Multiple-Station Radar Images

Dynamic analysis of in-orbit satellites is of interest for space situation applications. Some exploratory methods have been presented to analyze the state of attitude-steadied satellites in the complex space situation, but effectively estimating the dynamic parameters of spinning satellites remains a significant and interesting challenge nowadays. With decoupling target spin estimation from its trajectory motion, this paper proposes a novel dynamic estimation approach by using multiple-station inverse synthetic aperture radar (ISAR) images. In brief, quadratic phase characteristic, which is usually regarded as a negative factor for ISAR imagery in conventional algorithms, is now directly exploited to build an explicit expression of the relative motion between the spin in-orbit satellite and radar. Then, based on the developed image refocusing algorithm, these phase coefficients are extracted from the multiple-station images and substituted into the optimization of target dynamic estimation. In the end, target dynamic parameters, including its instantaneous attitude vector and spin speed, are estimated through particle swarm optimization. Experiment results illustrate the feasibility of the proposed algorithm. To some degree, this work also reflects the advantages of multiple-station ISAR system in some space applications.

Three-dimensional reconstruction for space targets with multistatic inverse synthetic aperture radar systems

In this paper, a three-dimensional (3D) reconstruction algorithm is proposed for space targets with multistatic inverse synthetic aperture radar (ISAR) systems. In the proposed algorithm, target 3D geometry can be obtained by solving the projection equations between the target 3D geometry and ISAR images. Specially, it is no need to perform cross-range scaling. To obtain the projection equations, the algorithm consists of two steps: establishing projection matrix and associating scattering centers. Firstly, observation angles of sensor can be estimated by kinematic formulas and coordinate systems transformation. Using azimuth and elevation angles of sensor relative to target, the projection matrix from target 3D geometry to ISAR images is established. Secondly, an association cost function based on projective transform and epipolar geometry is developed. As the cost function is an assignment with 0–1 linear programming, the Jonker-Volgenant algorithm is used to build a one-to-one correspondence between two scattering centers. Numerical results show the efficiency of the proposed algorithm.

Bistatic ISAR Imaging for Nonuniformly Rotating Targets

When a target undergoes nonuniform rotational motion (RM), conventional motion compensation (MOCOM) approaches for monostatic inverse synthetic aperture radar (ISAR) systems fail to correct the nonuniform RM error in bistatic radar systems; this failure is caused by nonlinear phase relationships between scatterers in bistatic ISAR (Bi-ISAR) systems. To address this problem, in this paper, we propose a new MOCOM framework for Bi-ISAR imaging of nonuniformly rotating targets. In the proposed method, a newly devised correction is performed to ensure successful RM compensation, followed by translational motion compensation. Because the phase relationships of the scatterers become virtually linear after this correction, nonuniform RM can be successfully converted into uniform RM. Namely, using the proposed method, translational and rotational motion errors are correctly removed, and focused Bi-ISAR images are obtained even for a target involved in nonuniform RM. Furthermore, for more effective use of Bi-ISAR images, a method to restore sheared Bi-ISAR images is exploited in the proposed framework. In the simulations and experiments, we determined that the proposed method can provide high-quality Bi-ISAR images for nonuniformly rotating targets.

Total rotational velocity estimation in a multistatic ISAR system

In this study, the authors report on a novel method to estimate the total rotational velocity of a non-cooperative moving target in a multi-static Inverse Synthetic Aperture Radar (ISAR) system. The method requires a system with at least four receivers spatially distributed such that their line-of-sight vectors are not coplanar. By using least squares optimisation, estimates of the magnitude of the effective rotational velocity `seen' by each receiver and trackfile information on the target trajectory and translational velocity are combined to determine the component due purely to the target's own rotational motion; an estimate for the total rotational velocity can thus be obtained, which can be useful for automatic target recognition. The multi-static nature of the system allows the technique to take into account the translational motion component of the total rotational velocity with some levels of robustness, which is not the case with other approaches. Simulated data results demonstrate the feasibility of the proposed method.

A Novel Wide Area Multiple Azimuth Beam ISAR Imaging System

A novel multiple azimuth beams (MAB) inverse synthetic aperture radar (ISAR) system, as well as, the corresponding processing algorithms are proposed in this paper, which is a promising technology for wide area surveillance (WAS). This system concept is intended to obtain wide area ISAR images of multiple moving targets, which would greatly increase the surveillance velocity range compared with the single beam system. The antenna transmits a sequence of high-gain and narrow radar beams to quickly scan a wide area, and receives the echoes from all the subswaths simultaneously. Two processing methods based on digital beamforming (DBF) are presented to separate the overlapped signals for achieving the wide area ISAR images. The performance of the proposed system is analyzed from the perspectives of the surveillance area, surveillance velocity range, and steering angle error. Finally, an exemplary ISAR system is presented and verified by the simulation experiments.

Three-Dimensional Imaging Method for Array ISAR Based on Sparse Bayesian Inference.

The problem of synthesis scatterers in inverse synthetic aperture radar (ISAR) make it difficult to realize high-resolution three-dimensional (3D) imaging. Radar array provides an available solution to this problem, but the resolution is restricted by limited aperture size and number of antennas, leading to deterioration of the 3D imaging performance. To solve these problems, we propose a novel 3D imaging method with an array ISAR system based on sparse Bayesian inference. First, the 3D imaging model using a sparse linear array is introduced. Then the elastic net estimation and Bayesian information criterion are introduced to fulfill model order selection automatically. Finally, the sparse Bayesian inference is adopted to realize super-resolution imaging and to get the 3D image of target of interest. The proposed method is used to process real radar data of a Ku band array ISAR system. The results show that the proposed method can effectively solve the problem of synthesis scatterers and realize super-resolution 3D imaging, which verify the practicality of our proposed method.

Joint multistatic THz imaging radars for standoff personnel screening

In response to the increasing threat of terrorism, standoff security screening of person-borne concealed weapons or contraband in public areas, such as airports and railway stations, is an urgent requirement; however, current solutions suffer from the limited field of view and the problem of security screening with interfering with the passenger flow. This paper proposes an imaging method that exploits the angular diversity of distributed multistatic terahertz (THz) radar network in combination with inverse synthetic aperture radar (ISAR) technique to realize high-resolution penetration imaging at a standoff range. The radar network is based on multistatic ISAR systems, and the multistatic ISAR system’s equivalent monostatic model is derived. According to the equivalent monostatic model, we develop the image formation algorithm and give the analytical expression of the cross-range resolution. Compared with conventional monostatic ISAR configuration, the analytical expression shows that the multistatic ISAR configuration can enhance the image’s cross-range resolution and the maximum enhanced factor is approximately equal to the number of radars in the multistatic system. Numerical simulations and experimental results agree well with the theoretical derivation. The proposed imaging approach offers a low-cost and flexible alternative to the present systems not only for security screening but also for noncooperative target imaging.

Presenting a New Technique for Multi-Target Tracking in Inverse Synthetic Aperture Radar based on PHD Filter in the Presence of Clutters

Abstract Using Probability Hypothesis Density (PHD) filtering, a novel approach is proposed in this paper for simultaneous tracking of multiple moving targets in received data by Inverse Synthetic Aperture Radar (ISAR) system. Since PHD filtering approach is implemented successively in prediction and update steps, its performance quality will obviously be higher in “Spotlight” imaging mode than in “Stripmap”. Thus, its application to Spotlight mode is generally more logical. The idea to integrate tracking capability into ISAR system processor is to sort radar received data to correct Range Cell Migration (RCM) prior to tracking operations. Clearly, Range Cell Migration Compensation (RCMC) approach is different from this approach in image formation process, in terms of their implementation phase. However, they are implemented in a similar way. As simulation results reveal, applying Range Cell Migration Compensation to the raw data received by ISAR before tracking operation, results in high quality tracking of moving targets.

Bayesian Bistatic ISAR Imaging for Targets with Complex Motion under Low SNR Condition.

This paper proposes a novel bistatic inverse synthetic aperture radar (ISAR) imaging algorithm for the target with complex motion under low signal to noise ratio (SNR) condition. Note the bistatic ISAR system generally suffers from a lower SNR than the monostatic one because of its non-mirror reflection geometry. A de-noising method, therefore, is proposed to improve SNR of range profiles, which accumulates the aligned range profiles non-coherently to obtain a window for noise suppression. Additionally, since the complex motion of target induces nonstationary Doppler, which is destructive to ISAR imaging, an optimal coherent processing interval (CPI) selection algorithm is further proposed to find out the interval where the Doppler is relatively stationary, so as to produce well-focused ISAR images. It utilizes the reassigned time-frequency (TF) method to obtain the high resolution instantaneous Doppler spectrum, and the minimum entropy criterion to select the optimal CPI, respectively. Note the selected CPI often contains too limited pulses to produce ISAR images with high resolution. A sparse aperture ISAR imaging method within the Bayesian framework is further proposed, which introduces the Laplacian scale mixture (LSM) model as the sparse prior, so as to reconstruct well-focused ISAR images with high resolution and low side lobes from the limited data. Compared with the traditional sparse Bayesian learning method, the proposed LSM based ISAR imaging performs superiorly on resolution improvement and noise reduction. Experimental results based on both simulated and measured data validate the effectiveness of the proposed algorithms.

High-resolution W-band ISAR imaging system utilizing a logic-operation-based photonic digital-to-analog converter.

W-band inverse synthetic aperture radar (ISAR) imaging systems are very useful for automatic target recognition and classification due to their high spatial resolution, high penetration and small antenna size. Broadband linear frequency modulated wave (LFMW) is usually applied to this system for its de-chirping characteristic. However, nearly all of the LFMW generated in electronic W-band ISAR system are based on multipliers and mixers, suffering seriously from electromagnetic interference (EMI) and timing jitter. And photonic-assisted LFMW generator reported before is always limited by bandwidth or time aperture. In this paper, for the first time, we propose and experimentally demonstrate a high-resolution W-band ISAR imaging system utilizing a novel logic-operation-based photonic digital-to-analog converter (LOPDAC). The equivalent sampling rate of the LOPDAC is twice as large as the rate of the digital driving signal. Thus, a broadband LFMW with a large time aperture can be generated by the LOPDAC. This LFMW is up-converted to W band with an optical frequency comb. After photonic-assisted de-chirping processing and data processing to the echo, a high-resolution two-dimension image can be obtained. Experimentally, W-band radar with a time-bandwidth product (TBWP) as large as 79200 (bandwidth 8 GHz; temporal duration 9.9 us) is established and investigated. Results show that the two-dimension (range and cross-range) imaging resolution is ~1.9 cm × ~1.6 cm with a sampling rate of 100 MSa/s in the receiver.

Broadband photonic ADC for microwave photonics-based radar receiver

A broadband photonic analog-to-digital converter (ADC) for X-band radar applications is proposed and experimentally demonstrated. An X-band signal with arbitrary waveform and a bandwidth up to 2 GHz can be synchronously sampled and processed due to the optical sampling structure. In the experiment, the chirp signal centered at 9 GHz with a bandwidth of 1.6 GHz is sampled and down-converted with a signal-to-noise ratio of 7.20 dB and an improved noise figure. Adopting the photonic ADC in the radar receiver and the above signal as the transmitted radar signal, an X-band inverse synthetic aperture radar system is set up, and the range and cross-range resolutions of 9.4 and 8.3 cm are obtained, respectively.

High Resolution Full-Aperture ISAR Processing through Modified Doppler History Based Motion Compensation.

A high resolution inverse synthetic aperture radar (ISAR) technique is presented using modified Doppler history based motion compensation. To this purpose, a novel wideband ISAR system is developed that accommodates parametric processing over extended aperture length. The proposed method is derived from an ISAR-to-SAR approach that makes use of high resolution spotlight SAR and sub-aperture recombination. It is dedicated to wide aperture ISAR imaging and exhibits robust performance against unstable targets having non-linear motions. We demonstrate that the Doppler histories of the full aperture ISAR echoes from disturbed targets are efficiently retrieved with good fitting models. Experiments have been conducted on real aircraft targets and the feasibility of the full aperture ISAR processing is verified through the acquisition of high resolution ISAR imagery.