Migration Through Resolution Cells Research Articles

Migration through Resolution Cell Correction and Sparse Aperture ISAR Imaging for Maneuvering Target Based on Whale Optimization Algorithm-Fast Iterative Shrinkage Thresholding Algorithm.

Targets faced by inverse synthetic aperture radar (ISAR) are often non-cooperative, with target maneuvering being the main manifestation of this non-cooperation. Maneuvers cause ISAR imaging results to be severely defocused, which can create huge difficulties in target identification. In addition, as the ISAR bandwidth continues to increase, the impact of migration through resolution cells (MTRC) on imaging results becomes more significant. Target non-cooperation may also result in sparse aperture, leading to the failure of traditional ISAR imaging algorithms. Therefore, this paper proposes an algorithm to realize MTRC correction and sparse aperture ISAR imaging for maneuvering targets simultaneously named whale optimization algorithm-fast iterative shrinkage thresholding algorithm (WOA-FISTA). In this algorithm, FISTA is used to perform MTRC correction and sparse aperture ISAR imaging efficiently and WOA is adopted to estimate the rotational parameter to eliminate the effects of maneuvering on imaging results. Experimental results based on simulation and measured datasets prove that the proposed algorithm implements sparse aperture ISAR imaging and MTRC correction for maneuvering targets simultaneously. The proposed algorithm achieves better results than traditional algorithms under different signal-to-noise ratio conditions.

A novel spaceborne ISAR imaging approach for space target with high-order translational motion compensation and spatial variant MTRC correction

ABSTRACT For spaceborne ISAR imaging of space targets, due to the high-speed relative motion between the radar and targets, both the translational and rotational motion exhibit the high-order characteristics. Conventional translational motion compensation (TMC) methods are ineffective in handling such high-order translational motion. Moreover, the migration through resolution cell (MTRC) stems from the presence of the high-order spatial variant phase of the echo signal, resulting in severe defocusing of ISAR images. In this paper, a novel spaceborne ISAR imaging approach for space targets is proposed, which incorporates the high-order TMC and the high-order MTRC correction. First, the slant range model for spaceborne ISAR imaging is derived as a third-order polynomial form. Based on this model, a modified high-order TMC method is proposed, which utilizes the minimum entropy method combined with the Broyden – Fletcher – Goldfarb – Shanno (BFGS) algorithm. The proposed method leverages orbital model information to obtain the initial TMC coefficients, enabling TMC to be completed more accurately and effectively. Then, a modified polynomial keystone transform (PKT) is proposed to correct the high-order MTRC. The PKT-based method effectively addresses both the high-order and first-order MTRC corrections simultaneously. Finally, a spaceborne ISAR imaging approach is proposed to obtain well-focused ISAR images. Simulated and real data results validate the analysis of the spaceborne ISAR imaging model and demonstrate the effectiveness of the spaceborne imaging approach for space targets proposed in this paper.

Unambiguous ISAR Imaging Method for Complex Maneuvering Group Targets

In inverse synthetic-aperture radar (ISAR) imaging, it is essential to deal with the Doppler ambiguity of group targets with complex maneuvers in order to avoid the bias of target position towards the actual value. Simultaneously, migration through resolution cell (MTRC) under the Doppler ambiguity is unable to be compensated for as a preprocessing. Traditional ISAR imaging methods for maneuvering targets, however, are undesirable to handle the severe deformation and defocusing in the imaging results induced by the Doppler ambiguity and MTRC. In this paper, we propose a novel and effective ISAR imaging method to improve the imaging quality by removing the Doppler ambiguity and compensating for the MTRC. Specifically, we first model the echo as a multi-component cubic phase signal (m-CPS) and design a high-order instantaneous autocorrelation function–generalized scaled Fourier transform (HIAF–GSCFT) to process the echo. This is to estimate the rotational parameters without MTRC compensation. Then, a maximum weighted contrast algorithm is used to remove the Doppler ambiguity, followed by reconstructing the echo. Compared with the existing method, the proposed method can accurately estimate the rotational parameters under the existing MTRCs and achieves a high-quality ISAR image for group targets, with complex maneuvers without Doppler ambiguity. Experiments of simulated and measured datasets validate its effectiveness and robustness for single target and group targets.

Image Defocus in an Airborne UWB VHR Microwave Photonic SAR: Analysis and Compensation

With the exploration of synthetic aperture radar (SAR), the requirements for its functionality, precision, and response time are inevitably increasing, in which the technical core is the generation, reception, and processing of wideband signals with low time cost. Owing to the excellent performance of modern photonics, such as the ultra-wide bandwidth (UWB), flat response, low transmission loss, fast analog signal processing, and microwave photonics (MWP) promises to be an appropriate solution to improve the capability of SAR in resolution, coverage, and efficiency. However, on the one hand, due to the high sensitivity of optical fiber, moisture, temperature, or physical vibration can produce an unknown extra propagation delay. On the other hand, the wavelength shift effect should be taken into consideration for the UWB system. Thereby, under very high resolution (VHR) circumstance, two-dimensional (2-D) defocus including migration through resolution cells (MTRC) and azimuth phase error (APE) becomes a challenge for MWP SAR imaging. Unfortunately, existing 2-D autofocus approaches concerning motion errors inherently fail for the commonly underlying assumption that the prominent nonsystematic residual range cell migration (RCM) is global in the azimuth time domain. In this article, we analyze the effects of the above-mentioned negative factors in the image processing of range migration algorithm (RMA) and reveal the structural characteristics of the 2-D phase errors. A novel two-step postprocessing compensation strategy is developed, and experiments on real data acquired by an airborne MWP SAR system demonstrate its effectiveness.

Removing Micro-Doppler Effect in ISAR Imaging by Promoting Joint Sparsity in Range Profile Sequences and the Time-Frequency Domain

The micro-Doppler effect induced by rotating parts interferes the inverse synthetic aperture radar (ISAR) imaging of the target’s rigid body heavily. To extract useful signals from rigid body and remove the micro-Doppler interference, this paper proposes a novel approach by promoting joint sparsity of the rigid body both in range profile sequences and time-frequency domain. The problem is formulated and modeled as a convex optimization with double joint sparsity penalty, and the exact solution can be obtained after multiple alternate iterations. In addition, the paper analyzes the effect of the scatterer’s linear migration through resolution cells (MTRC) on micro-Doppler removal. In order to avoid the signals from migrated rigid scatterers being removed together with the micro-Doppler signals, this paper proposes another improved reweighted method, in which the weights are designed to correlate slices with same frequency in neighboring range cells, to preserve migrated rigid scatterers and remove micro-Doppler interference meanwhile. Experimental results based on both synthetic and Electromagnetic simulated data demonstrate the validity of the proposed methods.

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.

An MTRC-AHP Compensation Algorithm for Bi-ISAR Imaging of Space Targets

For bistatic inverse synthetic aperture radar (Bi-ISAR) imaging of space targets, the impacts of scatterers’ migration through resolution cell (MTRC) and azimuth high-order phase (AHP) are becoming more severe, especially for a long coherent processing interval (CPI). In this paper, the movement of a scatterer is modeled as a quartic function under the restriction of the space target orbit, then an MTRC-AHP compensation algorithm is proposed. A fourth-order keystone transform is introduced to remove the MTRC firstly, then the residual AHP terms are compensated gradually via the azimuth compensation phase and fractional Fourier transform (FRFT). The impact of the orbit prediction error of the space target on the algorithm is analyzed theoretically. Numerical simulations illustrate the effectiveness of the proposed method and validation of the theoretical analysis.

ISAR Imaging of Maneuvering Target Based on the Estimation of Time Varying Amplitude With Gaussian Window

Due to the maneuverability of target’s motion in the inverse synthetic aperture radar (ISAR) imaging, the Doppler frequency of the received signal has the nonlinear time-varying characteristic. Under the circumstances, it is accurate enough to model the received signal of each range bin as a multicomponent quadratic frequency-modulated (QFM) signal. In this paper, the scaled Fourier transform (SCFT) is applied to obtain the phase parameters of the QFM signal. Owing to the phenomenon of the scatterers’ migration through resolution cell (MTRC) and the change of attitude angle, the amplitude of the received signal is no longer constant but time-varying. Thus, a novel and precise method using the adaptive Gaussian window is presented to estimate the time varying amplitude of the received signal. After that, the corresponding ISAR imaging algorithm is presented consequently. The validity of the proposed method is demonstrated by the simulated and real-data ISAR results.

High-Resolution Bistatic ISAR Imaging of a Space Target with Sparse Aperture

Due to the large size of space targets, migration through resolution cells (MTRC) are induced by a rotational motion in high-resolution bistatic inverse synthetic aperture radar (Bi-ISAR) systems. The inaccurate correction of MTRC degrades the quality of Bi-ISAR images. However, it is challenging to correct the MTRC where sparse aperture data exists for Bi-ISAR systems. A joint approach of MTRC correction and sparse high-resolution imaging for Bi-ISAR systems is presented in this paper. First, a Bi-ISAR imaging sparse model-related to MTRC is established based on compress sensing (CS). Second, the target image elements and noise are modeled as the complex Laplace prior, and the Gaussian prior, respectively. Finally, the high-resolution, well-focused image is obtained by the full Bayesian inference method, without manual adjustments of unknown parameters. Simulated results verify the effectiveness and robustness of the proposed algorithm.

ISAR Autofocus Imaging Algorithm for Maneuvering Targets Based on Phase Retrieval and Keystone Transform

In the current scenario of high-range resolution radar and noncooperative target, the rotational motion parameters of the target are unknown and migration through resolution cells (MTRC) is apparent in the obtained inverse synthetic aperture radar (ISAR)images, in both slant-range and cross-range directions. In the case of the high-speed maneuvering target with a small value of rotation, the phase retrieval algorithm can be applied to compensate for the translational motion to form an autofocusing image. However, when the target has a relatively large rotation angle during the coherent integration time, phase retrieval method cannot get an acceptable image for viewing and analysis as the location of the scatterer will not be true due to the Doppler shift imposed by the target’s rotational motion. In this paper, a novel ISAR imaging method for maneuvering targets based on phase retrieval and keystone transform is proposed, which can effectively solve the above problems. First, the keystone transform is used to solve the MTRC effects caused by the rotation component. Next, phase errors caused by the remaining translational motion will be removed by employing phase retrieval algorithm, allowing the scatterers are always kept in their range cells. Finally, the Doppler frequency shifts of scatterers will be time invariant in the phase of the received signal. Furthermore, this approach does not need to estimate the motion parameters of the target, which simplifies the processing steps. The simulated results demonstrate the validity of this method.

JOINT PROCESSING OF ENVELOPE ALIGNMENT AND PHASE COMPENSATION FOR ISAR IMAGING

Abstract. Range envelope alignment and phase compensation are spilt into two isolated parts in the classical methods of translational motion compensation in Inverse Synthetic Aperture Radar (ISAR) imaging. In classic method of the rotating object imaging, the two reference points of the envelope alignment and the Phase Difference (PD) estimation are probably not the same point, making it difficult to uncouple the coupling term by conducting the correction of Migration Through Resolution Cell (MTRC). In this paper, an improved approach of joint processing which chooses certain scattering point as the sole reference point is proposed to perform with utilizing the Prominent Point Processing (PPP) method. With this end in view, we firstly get the initial image using classical methods from which a certain scattering point can be chose. The envelope alignment and phase compensation using the selected scattering point as the same reference point are subsequently conducted. The keystone transform is thus smoothly applied to further improve imaging quality. Both simulation experiments and real data processing are provided to demonstrate the performance of the proposed method compared with classical method.

High resolution inverse synthetic aperture radar imaging of three-axis-stabilized space target by exploiting orbital and sparse priors**Project supported by the National Natural Science Foundation of China (Grant Nos. 61601496 and 61401024).

The development of inverse synthetic aperture radar (ISAR) imaging techniques is of notable significance for monitoring, tracking and identifying space targets in orbit. Usually, a well-focused ISAR image of a space target can be obtained in a deliberately selected imaging segment in which the target moves with only uniform planar rotation. However, in some imaging segments, the nonlinear range migration through resolution cells (MTRCs) and time-varying Doppler caused by the three-dimensional rotation of the target would degrade the ISAR imaging performance, and it is troublesome to realize accurate motion compensation with conventional methods. Especially in the case of low signal-to-noise ratio (SNR), the estimation of motion parameters is more difficult. In this paper, a novel algorithm for high-resolution ISAR imaging of a space target by using its precise ephemeris and orbital motion model is proposed. The innovative contributions are as follows. 1) The change of a scatterer projection position is described with the spatial-variant angles of imaging plane calculated based on the orbital motion model of the three-axis-stabilized space target. 2) A correction method of MTRC in slant- and cross-range dimensions for arbitrarily imaging segment is proposed. 3) Coarse compensation for translational motion using the precise ephemeris and the fine compensation for residual phase errors by using sparsity-driven autofocus method are introduced to achieve a high-resolution ISAR image. Simulation results confirm the effectiveness of the proposed method.

High-resolution inverse synthetic aperture radar imaging for large rotation angle targets based on segmented processing algorithm

In inverse synthetic aperture radar (ISAR) imaging, the migration through resolution cells (MTRCs) will occur when the rotation angle of the moving target is large, thereby degrading image resolution. To solve this problem, an ISAR imaging method based on segmented preprocessing is proposed. In this method, the echoes of large rotating target are divided into several small segments, and every segment can generate a low-resolution image without MTRCs. Then, each low-resolution image is rotated back to the original position. After image registration and phase compensation, a high-resolution image can be obtained. Simulation and real experiments show that the proposed algorithm can deal with the radar system with different range and cross-range resolutions and significantly compensate the MTRCs.

Maneuvering target imaging and scaling by using sparse inverse synthetic aperture

In recent years, there have been increasing interests in addressing the issue of high-resolution inverse synthetic aperture radar (ISAR) imaging from sparse aperture (SA) data. The non-uniform rotation property of maneuvering target introduces non-stationary echo modulation to exhibit two-dimensional (2-D) migration through resolution cells (MTRC), which increases the difficulty of SA-ISAR imaging. In this paper, we focus on ISAR imaging and scaling of maneuvering target for effective MTRC correction and SA synthesis. Under a scaled non-uniform Fourier dictionary to include MTRC, SA maneuvering target imaging is formatted as sparse representation with maximum a posterior (MAP) estimation. Then, sparse ISAR imaging joint with parameter estimation is solved by using a two-step procedure. The estimated rational parameters are used to rescale the reconstructed ISAR image to extract the 2-D target geometry. Finally, the experiments based on simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.

Inverse synthetic aperture radar imaging of maneuvering target based on cubic chirps model with time-varying amplitudes

Inverse synthetic aperture radar (ISAR) imaging of maneuvering target is a main topic in the field of radar signal processing, and the received signal in a range bin can usually be characterized as multicomponent cubic chirps with constant amplitudes after motion compensation. In fact, the phenomenon of migration through resolution cell (MTRC) often occurs for the target’s complex motion, and this will induce the time-varying character for the amplitudes of cubic chirps. An algorithm for the parameters estimation of multicomponent cubic chirps with time-varying amplitudes based on the extension form of match Fourier transform is proposed, and by using it in ISAR imaging of maneuvering target, the quality of images can be improved significantly compared with the constant amplitudes model. Results of simulated and real data validate the effectiveness of the algorithm in this paper.

High-Resolution Inverse Synthetic Aperture Radar Imaging and Scaling With Sparse Aperture

In high-resolution radar imaging, the rotational motion of targets generally produces migration through resolution cells (MTRC) in inverse synthetic aperture radar (ISAR) images. Usually, it is a challenge to realize accurate MTRC correction on sparse aperture (SA) data, which tends to degrade the performance of translational motion compensation and SA-imaging. In this paper, we present a novel algorithm for high-resolution ISAR imaging and scaling from SA data, which effectively incorporates the translational motion phase error and MTRC corrections. In this algorithm, the ISAR image formation is converted into a sparsity-driven optimization via maximum a posterior (MAP) estimation, where the statistics of an ISAR image is modeled as complex Laplace distribution to provide a sparse prior. The translational motion phase error compensation and cross-range MTRC correction are modeled as joint range-invariant and range-variant phase error corrections in the range-compressed phase history domain. Our proposed imaging approach is performed by a two-step process: 1) the range-invariant and range-variant phase error estimations using a metric of minimum entropy are employed and solved by using a coordinate descent method to realize a coarse phase error correction. Meanwhile, the rotational motion can be obtained from the estimation of range-variant phase errors, which is used for ISAR scaling in the cross-range dimension; 2) under a two-dimensional (2-D) Fourier-based dictionary by involving the slant-range MTRC, joint MTRC-corrected ISAR imaging and accurate phase adjustment are realized by solving the sparsity-driven optimization with SA data, where the residual phase errors are treated as model error and removed to achieve a fine correction. Finally, some experiments based on simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.

A Novel Imaging Method for Fast Rotating Targets Based on the Segmental Pseudo Keystone Transform

Fast rotating targets such as gimbaled antennas or propeller blades may cause migration through resolution cells (MTRC) of the high-resolution range profile during the imaging time, which makes the inverse synthetic aperture radar image smeared. To solve this problem, a novel imaging method for fast rotating targets is proposed in this paper. The method is based on the segmental pseudo Keystone transform, which is designed to realize MTRC correction. The fast realization is achieved by employing the discrete match Fourier transform, which makes the algorithm feasible and simple. Experiments with simulated radar data demonstrate the performance of the proposed method.

Uniform rotational motion compensation for inverse synthetic aperture radar with non-cooperative targets

In the current scenario of high-range resolution radars, the rotational motion of the target usually generates migration through resolution cells (MTRC) in the inverse synthetic aperture radar (ISAR) images. A technique to correct the MTRC in the case of uniform rotation rate is proposed. An estimation of the rotation vector of the non-cooperative targets is not required. The approach compensates the rotational motion in two steps: the slant-range rotation compensation (SRRC) and the cross-range rotation compensation (CRRC). CRRC is based on an extension of phase difference (PD) and on a robust method to delete outliers. The technique is verified both with simulated and live data from a millimetre-wave linear frequency-modulated continuous wave radar. A comparison with a minimum entropy-based technique is also made.

Migration Through Resolution Cell Compensation in ISAR Imaging

Range-Doppler (RD) processing is widely used in conventional inverse synthetic aperture radar (ISAR) imaging. The unwanted translational motion of moving targets is compensated by envelope alignment and autofocus. For existing ISAR imaging algorithms, the scatterers' migration through resolution cells (MTRC) caused by the rotational motion is usually ignored. With the improvement of resolution or the increase of target size, MTRC cannot be neglected. In this letter, the keystone formatting algorithm developed in SAR is used for the MTRC compensation in ISAR. Before the keystone formatting, coherent processing must be performed on the raw phase history data. An effective approach is proposed for this kind of coherent processing. Numerical examples are provided to demonstrate the performance of the proposed approach.

Compensation of scatterer migration through resolution cell in inverse synthetic aperture radar imaging

To obtain the inverse synthetic aperture radar image of a target, certain rotation angles of the target with respect to radar line of sight during the coherent integration interval are required, migration of scatterers will take place. Actually, scatterer migration through resolution cells (MTRC) will happen inevitably in high-resolution radar imaging, which will result in image resolution degradation. Scatterer MTRC is discussed, then a simple and an efficient algorithm, the MTRC compensation algorithm (MTRCCA), is proposed to compensate MTRC. The relationship between the MTRCCA, range–doppler and polar formatting algorithms is also discussed. ISAR images from simulated and real data measured in a microwave anechoic chamber are presented to validate the proposed algorithm.