Monostatic Inverse Synthetic Aperture Radar Research Articles

Using the CLEAN Method in Three-Dimensional Polarimetric ISAR Imaging Based on Volumetric Scattering Points

We developed a new technique for generating three-dimensional monostatic inverse synthetic aperture radar (ISAR) images using various types of polarimetric information on targets. To remove clutter around a target, we adopted the CLEAN method, in which only the main signals were reconstructed using an iterative algorithm. We conducted a simulation as follows: electric field data that were subjected to polarimetric scattering were obtained for the target using a full-wave electromagnetic analysis simulator. The linear polarization data of a 2 × 2 matrix were compressed into the linear to circular polarization data of a 2 × 1 matrix using the Jones vector based on circular polarization. On the grounds of the post-processed data, inverse Fourier transform was carried out to map scattering points to the spatial domain, after which the CLEAN method was used to retain only the primary scattering points.

MVFRnet: A Novel High-Accuracy Network for ISAR Air-Target Recognition via Multi-View Fusion

Inverse Synthetic Aperture Radar (ISAR) is a promising technique for air target imaging and recognition. However, the traditional monostatic ISAR only can provide partial features of the observed target, which is a challenge for high-accuracy recognition. In this paper, to improve the recognition accuracy of air targets, we propose a novel recognition network based on multi-view ISAR imaging and fusion, called Multi-View Fusion Recognition network (MVFRnet). The main structure of MVFRnet consists of two components, the image fusion module and the target recognition module. The fusion module is used for multi-view ISAR data and image preprocessing and mainly performs imaging spatial match, image registration, and weighted fusion. The recognition network consists of the Skip Connect Unit and the Gated Channel Transformation (GCT) attention module, where the Skip Connect Unit ensures the extraction of global depth features of the image and the attention module enhances the perception of shallow contour features of the image. In addition, MVFRnet has a strong perception of image details and suppresses the effect of noise. Finally, simulated and real data are used to verify the effectiveness of the proposed scheme. Multi-view ISAR echoes of six types of aircraft are produced by electromagnetic simulation software. In addition, we also build a millimeter wave ground-based bistatic ISAR experiment system and collect multi-view data from an aircraft model. The simulation and experiment results demonstrate that the proposed scheme can obtain a higher recognition accuracy compared to other state-of-the-art methods. The recognition accuracy can be improved by approximately 30% compared with traditional monostatic recognition.

Distributed inverse synthetic aperture radar imaging of ship target with complex motion

For ship targets with complex motion, it is difficult for the traditional monostatic inverse synthetic aperture radar (ISAR) imaging to improve the cross-range resolution by increasing of accumulation time. In this paper, a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target. Multiple stations are used to observe the target in a short time, thereby the effect of incoherence caused by the complex motion of the ship can be reduced. The signal model of ship target with three-dimensional (3-D) rotation is constructed firstly. Then detailed analysis about the improvement of cross-range resolution is presented. Afterward, we propose the methods of parameters estimation to solve the problem of the overlap or gap, which will cause a loss of resolution and is necessary for subsequent processing. Besides, the compressed sensing (CS) method is applied to reconstruct the echoes with gaps. Finally, numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.

Multistatic inverse synthetic aperture radar imaging based on parametric block-sparse reconstruction

By combining the data of different spatially distributed sensors, multistatic inverse synthetic aperture radar (ISAR) can provide more stable imaging results compared with monostatic ISAR. In most previous studies of multistatic ISAR imaging, the scatterers on the target are modeled as isotropic points and a conventional monostatic ISAR imaging method is directly applied after rearranging the data of multiple sensors, which will result in the degradation of image quality, especially when the measurements are limited. In practice, the complex amplitude of the scatterer is usually strongly angle dependent; therefore, the echo of different sensors cannot be assumed to be coherent. We consider the fluctuation of the radar cross section and propose a method based on compressed sensing (CS) for multistatic ISAR imaging. By utilizing the block orthogonal matching pursuit (BOMP) method to reconstruct the target image, the requirement of coherence between different sensors can be eliminated. Moreover, in order to apply the CS method, a two-step target motion estimation approach is also presented. A coarse motion estimation method is first applied by tracking the target trajectory with the distance-sum measurement. Then, associating the gradient-based optimization algorithm with BOMP, a parametric block-sparse reconstruction method is developed to jointly correct the residual position error and recover the target image with incoherent echo. Simulation results show the effectiveness of the proposed method.

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.

Bistatic ISAR Sparse Imaging Method for High-Speed Moving Target Based on Dechirping Processing

Bistatic inverse synthetic aperture radar (ISAR) can increase the probability of tracking the high-speed target and provide more angle information than monostatic ISAR. However, bistatic ISAR suffers from a serious defocusing problem, resulting from the high-speed motion. Furthermore, the inherent geometry distortion and calibration problems make bistatic ISAR (B-ISAR) imaging more complex. In response to these problems, we propose a bistatic ISAR imaging method for high-speed moving target with geometric distortion correction and calibration based on dechirping processing. At first, based on the motion decomposition idea, the B-ISAR echo model of the high-speed moving target is established. Then, by analyzing the imaging mechanism of the Range-Doppler algorithm (RDA), we eliminate the phase items influencing the imaging quality with speed compensation and Doppler compensation. After that, the analytic formula of the geometric distortion factor and calibration factor are deduced, which helps transform the geometric correction and calibration problem into a parameter estimation problem. Finally, with the sparsity of the scattering points, the required parameters are solved using the expectation maximization (EM) algorithm based on the maximum a posteriori probability criterion. With the estimated parameters, a clear B-ISAR image of a high-speed moving target with geometric correction and calibration is obtained. The simulations show that the proposed method has a better resolution and simultaneously attains geometric correction and calibration of the image.

Bistatic ISAR Imaging and Scaling of Highly Maneuvering Target With Complex Motion via Compressive Sensing

The bistatic configuration used for inverse synthetic aperture radar (ISAR) imaging has attracted considerable attention because of its potential for overcoming certain monostatic ISAR imaging limitations. However, translational motion compensation (TMC) and rotational motion compensation (RMC) are the most fundamental requirements for both bistatic ISAR (Bi-ISAR) and monostatic ISAR imaging to obtain the high levels of image resolution desired. Moreover, range and cross-range scaling (RCRS) and bistatic distortion correction (BDC) are essential functionalities for the efficient use of Bi-ISAR images in applications. In this paper, a novel approach to sparse aperture (SA) Bi-ISAR imaging is presented for simultaneously performing TMC, RMC, RCRS, and BDC on maneuvering targets based on compressive sensing. Instead of solving conventional optimization problems constrained by the sparsity of the signals, the proposed method utilizes sensing matrix estimation technique for Bi-ISAR image reconstruction using parametric signal model reconstruction by looking for the basis functions that best represent the behavior of sensing dictionary matrix comprised of the observed SA data. The reconstruction of the sensing matrix is based on a modified orthogonal matching pursuit (MOMP)-type basis function-searching scheme. Finally, we generate a focused and scaled Bi-ISAR image from the complete Bi-ISAR signal recovered using the proposed method. Several simulation results reveals that the proposed method is very efficient in forming Bi-ISAR images of high-speed maneuvering targets in terms of the Bi-ISAR signal reconstruction accuracy.

Bistatic inverse synthetic aperture radar imaging method for the high-speed motion target

Bistatic inverse synthetic aperture radar (ISAR) can help image the high-speed target for its advantage in tracking and more observation angle to provide more information than monostatic ISAR. However, the complex image geometry makes it difficult to achieve a clear image of the target with geometry distortion correction and calibration. Furthermore, high-speed motion will make the image blurred or defocussed. To address these problems, a bistatic ISAR (B-ISAR) imaging method for high-speed motion target with geometric distortion correction and calibration is proposed. According to the motion decomposition idea, we established the B-ISAR echo model of the high-speed motion target. Then, based on the range Doppler algorithm, we deduce the analytic formula of the geometric distortion factor and calibration factor, and transform the imaging problem into a parameter estimation problem. With the sparsity of the scattering points, the required parameters are solved using the expectation maximization algorithm based on the maximum a posteriori probability criterion. With the estimated parameters, a clear B-ISAR image of a high-speed motion target with geometric correction and calibration is obtained. The simulations show that the proposed method has better resolution and simultaneously attains geometric distortion correction and calibration of the image.

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.

Distributed ISAR Subimage Fusion of Nonuniform Rotating Target Based on Matching Fourier Transform.

In real applications, the image quality of the conventional monostatic Inverse Synthetic Aperture Radar (ISAR) for the maneuvering target is subject to the strong fluctuation of Radar Cross Section (RCS), as the target aspect varies enormously. Meanwhile, the maneuvering target introduces nonuniform rotation after translation motion compensation which degrades the imaging performance of the conventional Fourier Transform (FT)-based method in the cross-range dimension. In this paper, a method which combines the distributed ISAR technique and the Matching Fourier Transform (MFT) is proposed to overcome these problems. Firstly, according to the characteristics of the distributed ISAR, the multiple channel echoes of the nonuniform rotation target from different observation angles can be acquired. Then, by applying the MFT to the echo of each channel, the defocused problem of nonuniform rotation target which is inevitable by using the FT-based imaging method can be avoided. Finally, after preprocessing, scaling and rotation of all subimages, the noncoherent fusion image containing all the RCS information in all channels can be obtained. The accumulation coefficients of all subimages are calculated adaptively according to the their image qualities. Simulation and experimental data are used to validate the effectiveness of the proposed approach, and fusion image with improved recognizability can be obtained. Therefore, by using the distributed ISAR technique and MFT, subimages of high-maneuvering target from different observation angles can be obtained. Meanwhile, by employing the adaptive subimage fusion method, the RCS fluctuation can be alleviated and more recognizable final image can be obtained.

Clutter Suppression and High-Resolution Imaging of Noncooperative Ground Targets for Bistatic Airborne Radar

In a recent paper, the problem of inverse synthetic aperture radar (ISAR) imaging moving ground targets was discussed and an effective solution based on a novel joint space-time adaptive processing (STAP)-ISAR formulation was proposed. In the case of bistatic geometry, ISAR imaging can be simply and effectively enabled via the bistatically equivalent monostatic theory, which allows for monostatic ISAR processing to be used to form bistatic ISAR images. However, the clutter nonstationary introduced by the bistatic geometry strongly degraded STAP performances if a monostatic STAP processing is used. In this paper, a new joint STAP-ISAR processing is introduced that works in the bistatic case. Theoretical figures and numerical simulations are used to prove the effectiveness of the proposed approach.

Bistatic-ISAR Distortion Correction and Range and Cross-Range Scaling

The bistatic configuration used for inverse synthetic aperture radar (ISAR) imaging has attracted much attention because of its potential to overcome the certain limitations of monostatic ISAR imaging. However, range and cross-range scaling and bistatic distortion correction are essential for the efficient use of a bistatic ISAR (Bi-ISAR) image in their applications. In this paper, we introduce a novel range and cross-range scaling technique and bistatic distortion correction method for the restoration of a sheared (Bi-ISAR) image. The proposed method is composed of five stages: 1) extraction of the prominent scatterer using the range-bin selection method; 2) determination of the coefficients of the phase-history data in the selected range bin; 3) estimation of rotation center of the target using the optimization procedures via the particle swarm optimization algorithm; 4) range and cross-range scaling of (Bi-ISAR) image; and 5) restoration of the bistatic distortion that caused the sheared (Bi-ISAR) image. Finally, the proposed method can generate a well-scaled and restored (Bi-ISAR) image. An outstanding advantage of this method is that it requires no prior information about the bistatic configuration. Several examples are presented to validate the effectiveness of the proposed method.

Bistatic inverse synthetic aperture radar imaging method for maneuvering targets

Bistatic inverse synthetic aperture radar (ISAR) is an efficient geometric configuration of ISAR and can provide complementary information to monostatic ISAR. However, bistatic ISAR suffers from a serious defocusing problem and distortion problem for maneuvering targets. We propose a method to solve these problems. First, cubic chirplet decomposition based on Keystone transform (KTCCD) is proposed to eliminate the defocusing problem. The echo is assumed as a combination of cubic chirplet atoms, and Keystone transformation is utilized to estimate the parameters for each atom. Then, a method based on distortion term estimation is proposed to eliminate the distortion problem. The distortion terms in certain range bins are expressed by the initial frequency and the chirp rate, and the distortion terms in other range bins are fitted by the ordinary least square algorithm. Simulation results validate the theoretical analysis and show the effectiveness of our method.

Defocusing and distortion elimination for shipborne bistatic ISAR

ABSTRACTShipborne bistatic inverse synthetic aperture radar (ISAR), with a stationary and visible transmitter on land and a mobile and stealthy receiver on a ship with complex 3-D rotations is a strategic asset which can provide complementary information to monostatic ISAR. However, it must first overcome the serious problems of defocusing and distortion due to the time-varying bistatic angle. In this letter, an improved cubic chirplet decomposition method is proposed to solve the defocusing problem. By decomposing the ISAR echo into cubic chirplet atoms and estimating the parameters for each term, higher-order defocusing terms can be eliminated. Moreover, a novel method based on linked scatterers is put forward to solve the distortion problem. The method utilizes ‘linked scatterers’ from monostatic ISAR image to calculate and compensate the distortion angle. The effectiveness of the proposed methods is verified by the simulation results.

Analysis of synchronization errors for InISAR on separated platforms

Bistatic inverse synthetic aperture radar (BiISAR) imaging and interferometric inverse synthetic aperture radar (InISAR) imaging can provide complementary information to monostatic inverse synthetic aperture radar (MoISAR) imaging. Time synchronization is a requirement for both systems. This paper focuses on the problem of the time synchronization in the BiISAR and InISAR imaging with a polynomial time synchronization error model (PTSEM) in theory. The effects of the time synchronization errors to the range and azimuth compression with the synchronization errors are analyzed in detail. A phase error model transferred from the synchronization errors to the interferometric error is established. A simulation displays the results of the analysis.

Interferometric inverse synthetic aperture radar imaging for space targets based on wideband direct sampling using two antennas

Interferometric inverse synthetic aperture radar (InISAR) imaging provides complementary information to monostatic inverse synthetic aperture radar (ISAR) imaging. This paper proposes a new InISAR imaging system for space targets based on wideband direct sampling using two antennas. The system is easy to realize in engineering since the motion trajectory of space targets can be known in advance, which is simpler than that of three receivers. In the preprocessing step, high speed movement compensation is carried out by designing an adaptive matched filter containing speed that is obtained from the narrow band information. Then, the coherent processing and keystone transform for ISAR imaging are adopted to reserve the phase history of each antenna. Through appropriate collocation of the system, image registration and phase unwrapping can be avoided. Considering the situation not to be satisfied, the influence of baseline variance is analyzed and compensation method is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Experimental results prove the validity of the analysis and the three-dimensional imaging algorithm.

High resolution ISAR imaging in receiver centered region area in bistatic radar

Aim at overcoming limitations from a single fixed aspect in monostatic inverse synthetic aperture radar (ISAR) system, bistatic radar system becomes a hot research topic in ISAR imaging. However, it is become more difficult to obtain a high resolution ISAR image of maneuvering target in receiver centered region area of bistatic radar for time varying bistastic angle and equivalent line of sight (LOS) aspect. In this paper, a super-resolution imaging method based on Radon transform combined with time chirp distribution search (TCDS) procedure is proposed. This method attempts to estimate the chirp rate and its changing rate corresponding to high-order phase terms in cross range. After compensating the phase error of high order, more scattering centers of target are extracted and high resolution imaging is generated by Radon-TCDS-Relax algorithm. Simulation results are provided to demonstrate the performance of the proposed method.

On Bistatic Inverse Synthetic Aperture Radar

The use of multiple radar configurations can overcome some of the geometrical limitations that exist when obtaining radar images of a target using inverse synthetic aperture radar (ISAR) techniques. It is shown here how a particular bistatic configuration can produce three view angles and three ISAR images simultaneously. A new ISAR signal model is proposed and the applicability of employing existing monostatic ISAR techniques to bistatic configurations is analytically demonstrated. An analysis of the distortion introduced by the bistatic geometry to the ISAR image point spread function (PSF) is then carried out and the limits of the applicability of ISAR techniques (without the introduction of additional signal processing) are found and discussed. Simulations and proof of concept experimental data are also provided that support the theory.