Cross-range Scaling Research Articles

Sparse Aperture ISAR Imaging and Cross-Range Scaling of Maneuvering Targets Based on Sparse CICPF Method

Sparse Aperture ISAR Imaging and Cross-Range Scaling of Maneuvering Targets Based on Sparse CICPF Method

Staring-imaging satellite pointing estimation based on sequential ISAR images

Pointing estimation for spacecraft using Inverse Synthetic Aperture Radar (ISAR) images plays a significant role in space situational awareness and surveillance. However, feature extraction and cross-range scaling of ISAR images create bottlenecks that limit performances of current estimation methods. Especially, the emergence of staring imaging satellites, characterized by complex kinematic behaviors, presents a novel challenge to this task. To address these issues, this article proposes a pointing estimation method based on Convolutional Neural Networks (CNNs) and a numerical optimization algorithm. A satellite’s main axis, which is extracted from ISAR images by a proposed Semantic Axis Region Regression Net (SARRN), is chosen for investigation in this article due to its unique structure. Specifically, considering the kinematic characteristic of the staring satellite, an ISAR imaging model is established to bridge the target pointing and the extracted axes. Based on the imaging model, pointing estimation and cross-range scaling can be described as a maximum likelihood estimation problem, and an iterative optimization algorithm modified by using the strategy of random sampling-consistency check and weighted least squares is proposed to solve this problem. Finally, the pointing of targets and the cross-range scaling factors of ISAR images are obtained. Simulation experiments based on actual satellite orbital parameters verify the effectiveness of the proposed method. This work can improve the performance of satellite reconnaissance warning, while accurate cross-range scaling can provide a basis for subsequent data processes such as 3D reconstruction and attitude estimation.

Fast Iterative Wiener Filter-Based ISAR Imaging and Cross-Range Scaling With Periodically Gapped CPI

Fast Iterative Wiener Filter-Based ISAR Imaging and Cross-Range Scaling With Periodically Gapped CPI

One-Bit Cross-Range Scaling Approach to ISAR Imaging

One-Bit Cross-Range Scaling Approach to ISAR Imaging

Slow-Spinning Spacecraft Cross-Range Scaling and Attitude Estimation Based on Sequential ISAR Images

Slow-Spinning Spacecraft Cross-Range Scaling and Attitude Estimation Based on Sequential ISAR Images

GNSS-Based Passive Inverse SAR Imaging

The utilization of global navigation satellite system (GNSS) signals for remote sensing has been a hot topic recently. In this article, the feasibility of the GNSS-based passive inverse synthetic aperture radar (P-ISAR) is analyzed. GNSS-based P-ISAR can generate the two-dimensional image of a moving target, providing an estimation of the target size, which is very important information in target recognition. An effective GNSS-based P-ISAR moving target imaging algorithm is proposed. First, a precise direct path interference (DPI) suppression method is derived to eliminate the DPI power in the detection channel. Then, the P-ISAR signal processing method is established. Due to the large synthetic aperture time, the Doppler profile of the ISAR image will defocus if directly performing the Fourier transform. As a solution, a parametric autofocusing and cross-range scaling algorithm is specially tailored for the GNSS-based P-ISAR. The proposed algorithm cannot only focus and scale the ISAR image, but also provide an estimation of the cross-range velocity of the target. Simulation with an airplane target is designed to test the signal processing method. Finally, an experiment is conducted with a civil airplane as the target and GPS satellites as the illumination source. Focused ISAR image is successfully acquired. The estimated length and velocity of the target are approximately consistent with ground truth, which are obtained by the flight record. The potential of the GNSS-based P-ISAR on multistatic operations is also illustrated by the fusion of the ISAR images obtained using different satellites as illumination sources.

A novel approach for squint InISAR imaging with dual-antenna configuration

The image distortion arises in the Interferometric Inverse Synthetic Aperture Radar (InISAR) three-dimensional (3D) imagery when the radar works in squint-mode. Existing squint InISAR imaging methods suffer from high computational complexity and poor imaging quality due to the vertical Coordinates Transformation (CT) and iterative operations for rectifying the 3D image distortion. To address this issue, we propose an imaging method for squint InISAR with two antennas. Firstly, the cross-range scaling is used to obtain initial horizontal coordinates of the target. Then, the interferometric phase is used to obtain the altitude coordinates of the target, and hence a 3D image of the target is formed. Finally, the CT is applied to rectify the 3D image distortion by correcting the acquired horizontal and vertical and altitude coordinates of the target. The dual-antenna configuration reduces the complexity of the InISAR system. We perform extensive simulations to demonstrate the effectiveness of the proposed dual-antenna squint InISAR imaging method.

Passive bistatic inverse synthetic aperture radar imaging and cross-range scaling of maneuvering target based on a noise-resistant parameters estimation algorithm

For passive bistatic inverse synthetic aperture radar (PB-ISAR) imaging of maneuvering targets, the complex motion of the target causes non-uniform time-varying bistatic angle and non-uniform rotation of the target, which leads to the severe bistatic distortion and defocusing in the generated ISAR image. To obtain a focused, well-scaled PB-ISAR image that can show the accurate shape and size of the target, the essential issues, including bistatic distortion, image defocus, and range and cross-range scaling (RCRS), must be addressed. An innovative PB-ISAR imaging and cross-range scaling method is proposed for obtaining ISAR image of the maneuvering targets under low SNR condition. First, we estimate the multi-dimensional parameters to approximate the non-uniform time-varying bistatic angle and non-uniform rotation of the target. Then, based on the estimated parameters, the bistatic distortion correction, defocus terms elimination, and RCRS can be performed subsequently. Finally, a focused and well-scaled PB-ISAR image of the target can be obtained. The proposed method can work under a low signal-to-noise ratio. The simulation results validate the effectiveness of the proposed method.

특징점 추출 및 매칭을 이용한 ISAR 영상의 수직-거리 스케일링 기법 연구

A method that utilizes two sequential inverse synthetic aperture radar (ISAR) images to estimate the rotation velocity of the target and perform cross-range scaling of ISAR images is proposed. First, features/scatterers that are robust against the change in aspect angle and the scintillation between two sequential ISAR images are extracted. Next, extracted features are matched such that the same feature corresponds between the two sequential ISAR images. To accomplish this, scale-invariant feature transform is adopted for feature extraction, followed by feature matching through nearest-neighbor distance ratio and random sample consensus techniques. In this way, a homography between two sequential ISAR images can be obtained and the rotational velocity of the target can be deduced without prior knowledge of the equivalent rotational center of the target. To demonstrate the effectiveness of the proposed method, the results of a simulation dataset for point scatterers are provided.

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.

A Novel ISAR Imaging and Scaling Approach for Maneuvering Targets Based on High-Accuracy Phase Parameter Estimation Algorithm

For inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, the Doppler frequency induced by an arbitrary scatterer on the target is time-varying, and hence, the traditional range-Doppler (RD) algorithm is not appropriate for obtaining focusing ISAR images. In such a scenario, a novel ISAR technique, called the range instantaneous Doppler derivative (RIDD) algorithm, has been recently proposed, and two different kinds of well-focused ISAR images, named range-Doppler centroid (RDC) frequency image and range-Doppler frequency rate (RDR) image, can be obtained. In order to improve the accuracy of the target classification and recognition, the scaling approach for the RIDD algorithm must be taken into consideration. In this article, the point spread function (PSF) representations and cross-range scaling factors of the RDC image and the RDR image obtained by the RIDD algorithm are demonstrated analytically. On the basis of the PSFs and cross-range scaling factors, a novel imaging and scaling approach for the RIDD algorithm in the presence of a low SNR environment based on smoothed integrated high-resolution time–frequency-rate representation (SIHR) combined with coherent integrated smoothed generalized cubic phase function (CISCF) is proposed. As the proposed algorithm has high estimation accuracy and good antinoise capability, precise parameter estimation of the received signal can be achieved. Hence, high-quality scaled RDC and RDR images of the target can be reconstructed by the proposed approach. Experimental results of simulated data and real measured data verify the correctness of the PSF representations and demonstrate the effectiveness of the imaging and scaling approach proposed in this article.

Identification of ships moving in formation by HFSWR using an ISAR cross-range imaging algorithm

ABSTRACT High-frequency surface wave radar (HFSWR) has been widely used for ship detection to improve human marine activities. However, the azimuthal resolution is a major challenge for ship detection in HFSWR. Synthetic aperture technology can improve azimuthal resolution, which is different from increasing the size of the antenna array directly in practice. A new method to improve HFSWR azimuthal resolution for ships moving in formation is proposed. The proposed method extends inverse synthetic aperture radar (ISAR) cross-range imaging method to HFSWR, allowing ships in formation to be distinguished from each other in the cross-range domain. In the framework of HFSWR cross-range imaging, the motion of the ship formation is regarded as a rotating turntable by motion compensation. Based on the turntable configuration, the relationship between the cross-range domain and Doppler frequency can be built precisely. Then, the cross-range profile is obtained from the echo data by Fourier transform, and the cross-range spacing between ships can be estimated by the cross-range scaling. The simulated results demonstrate the effectiveness of the proposed method. The present work provides a new idea to improve the azimuthal resolution of HFSWR.

A modified ISAR cross‐range scaling method based on iterative principle component analysis

High-resolution inverse synthetic aperture radar (ISAR) imaging can produce electromagnetic images of a target in the range and cross-range domain. However, to make full use of an ISAR image in target detection and recognition, we need to rescale the image in a homogeneous range and cross-range domain, and further, to estimate the effective rotational velocity (RV) of the target. A precise ISAR image cross-range scaling method is proposed. A candidate RV is obtained based on the bisection method. Then, the effective rotation angle (RA) between two sequential rescaled images is characterised by the RA between the major axes of the images. These axes are extracted by principle component analysis (PCA). A precise estimation of the RV is obtained through iterative PCA and bisection. Simulated and real data experimental results validate the effectiveness of the proposed method.

Robust ISAR Cross-Range Scaling via Two-Step Rotation Velocity Estimation

To obtain exact size of non-cooperative target in ISAR images, an accurate cross-range scaling (CRS) should be performed. To do this, an image based approach, which exploits two sequential ISAR images based on the scale and rotational relationship between them, has been adopted in the existing ISAR CRS methods. However, they have two major problems: 1) unknown effective rotation center (ERC) of non-cooperative target, and 2) performance degradation owing to the scintillation of two ISAR images. To address these issues, in this paper, we propose a new CRS method, mainly consisting of two steps: 1) coarse estimation of rotation velocity (RV) in range-Doppler (RD) domain after feature extraction and matching, and 2) using the estimate in Step1, fine RV estimation via singular value decomposition (SVD) in range/cross-range (RC) domain. Furthermore, experimental results based on simulated and real measured data are provided to demonstrate the effectiveness of the proposed method.

ISAR cross-range scaling based on the MUSIC technique

Cross-range scaling plays an important role in the inverse synthetic aperture radar (ISAR) imaging. Many of the published cross-range scaling algorithms are based on the fast Fourier transformation (FFT). However, the FFT technique is resolution limited, so that the FFT-based algorithms will fail in the rotation velocity (RV) estimation of the slow rotation target. In this paper, we propose an accurate cross-range scaling algorithm based on the multiple signal classification (MUSIC) method. We first select some range bins with the mono-component linear frequency modulated (LFM) signal model. Then, we dechirp the signal of each selected range bin into the form of sinusoidal signal, and utilize the super-resolution MUSIC technique to accurately estimate the frequency. After processing all the range bins, a linear relationship related to the RV can be obtained. Eventually, the ISAR image can be scaled. The proposal can precisely estimate the small RV of the slow rotation target with low computational complexity. Furthermore, the proposal can also be used in the case of cross-range scaling for the sparse aperture data. Experimental results with the simulated and raw data validate the superiority of the novel method.

ISAR imaging and cross-range scaling of maneuvering targets using the scaled transform

In this paper, a novel method based on the scaled transform is proposed for the ISAR imaging and cross-range scaling of a maneuvering target with uniform rotating acceleration. Firstly, the cross-range signals in each range cell can be modeled as multiple chirp signals. The scaled transform is utilized to eliminate the coupling with the slow time and lag time in the time-dependent autocorrelation function of multiple chirp signals. Then the 2-D accumulation plane can be obtained by the 2-D FFT and the cross-range profile can be obtained by a projection from the 2-D accumulation plane to the azimuth dimension. Meanwhile, the initial frequency and chirp rate of each scatterer can be estimated by the corresponding perk in the 2-D accumulation plane. Finally, the rotating motion parameters are estimated by the least square method and the cross-range scaling is performed. Simulation results prove the effectiveness of the proposed method.

An ISAR imaging and cross-range scaling method based on phase difference and improved axis rotation transform

In this paper, a novel cross-range scaling method for inverse synthetic aperture radar imaging is proposed to estimate rotation angular velocity of the target by fully integrating the energy of all the target scatterers. Firstly, the phase difference is utilized to integrate the scatterers located at a same range cell into one point. Then, the improved axis rotation technique is adopted to transform the energy of all the scatterers into one sharp peak, with the peak position providing the estimation of rotational velocity of the target. Finally, a well-focused and scaled target image can be obtained with the estimated rotational velocity. Compared with the conventional methods, the proposed method can obtain high scaling precision under relatively low signal-to-noise ratio environment since the energy of all target's scatterers can be fully exploited. Both simulation experiment and measured data results are provided to verify the effectiveness of the proposed algorithm.

Rotation Parameters Estimation and Cross-Range Scaling Research for Range Instantaneous Doppler ISAR Images

The maneuverability of targets cannot be neglected in many circumstances for Inverse Synthetic Aperture Radar (ISAR) imaging procedure. For these circumstances, the Range Instantaneous Doppler (RID) algorithm is required to form the well-focused ISAR images. Simultaneously, as the inevitable means of obtaining the target’s cross-range size, the cross-range scaling approach for the RID images also needs to be considered consequently. Since there are few cross-range scaling methods focused on the RID images, we propose a novel method in this paper based on the phase coefficients estimation and scatterers pairing process to solve the problem. Without the special requirements for the scatterers or complicated optimization process, the proposed approach is widely adaptive and efficient. Otherwise, besides the novel estimation method for the rotation parameters, we also propose the novel technique for calculating the cross-range scaling factor of the RID images, which is quite different from that of the Range Doppler (RD) images. Finally, by using the recommended RID imaging algorithm and the proposed cross-range scaling approach, the results of ISAR imaging and cross-range scaling experiments on the simulation and real-data experiment are represented, which demonstrate the effectiveness of the proposed approach in this paper.

High Precision Cross-Range Scaling and 3D Geometry Reconstruction of ISAR Targets Based on Geometrical Analysis

Cross-range scaling of sequential inverse synthetic aperture radar (ISAR) images is a vital problem for the three-dimensional (3D) reconstruction of spatial targets. Specifically, since the angular velocity of spatial targets cannot be accurately estimated due to their non-cooperative nature, the obtained cross-range coordinates of the scattering points often have non-negligible errors. The errors may result in a serious distortion of the reconstructed geometry of the targets, which makes consequent target recognition and classification unreliable. To tackle this problem, via geometrical analysis, the relationship between the cross-range projection vector and the range projection vector is revealed for the first time, based on which a novel algorithm is proposed to iteratively scale the cross-range coordinates with no need for estimating the angular velocity of the spatial targets. Experimental simulations show that the proposed algorithm not only provides a higher accuracy of 3D reconstruction, but also has a lower computational complexity compared with conventional algorithm.

Cross-Range Scaling of ISAR Image Generated by the Range-Chirp Rate Algorithm for the Maneuvering Target

For Inverse Synthetic Aperture Radar (ISAR) imaging of target with moderate maneuverability, the received signal in a range bin can be characterized as multi-component linear frequency modulated (LFM) signal. In this paper, we find that the chirp rate of the LFM signal is proportional to the cross-range coordinate of the corresponding scatterer when the range effect has been compensated completely. Then, a novel ISAR imaging algorithm, named as Range-Chirp Rate (RCR), is proposed in this paper, which only uses the chirp rates to form the cross-range image. After that, two key problems in the RCR imaging process, including the selection of the adjustment factor and the image distortion compensation, are derived consequently. Finally, the solutions for the problems are proposed, and the corresponding cross-range scaling method for the RCR ISAR image is proposed simultaneously. Results of simulated and real measured data demonstrate the effectiveness of the method in this paper.