ISAR Imaging Of Targets Research Articles

High-success-rate ISAR imaging of maneuvering targets with a robust optimal imaging time interval selection algorithm

High-success-rate ISAR imaging of maneuvering targets with a robust optimal imaging time interval selection algorithm

Analysis of time-variant IPP and ISAR imaging for non-cooperative targets with highly maneuvering motion

Analysis of time-variant IPP and ISAR imaging for non-cooperative targets with highly maneuvering motion

ISAR imaging of maneuvering targets using synchronous extraction transformation under low SNR

ISAR imaging of maneuvering targets using synchronous extraction transformation under low SNR

Translational Motion Compensation Method for ISAR Imaging of Air Maneuvering Weak Targets Based on CV-GRUNet

Translational Motion Compensation Method for ISAR Imaging of Air Maneuvering Weak Targets Based on CV-GRUNet

3-D High-Resolution ISAR Imaging for Noncooperative Air Targets

3-D High-Resolution ISAR Imaging for Noncooperative Air Targets

Few-shot Classification for ISAR Images of Space Targets by Complexvalued Patch Graph Transformer

Few-shot Classification for ISAR Images of Space Targets by Complexvalued Patch Graph Transformer

GEO Targets ISAR Imaging With Joint Intra-Pulse and Inter-Pulse High-Order Motion Compensation and Sub-Aperture Image Fusion at ULCPI

GEO Targets ISAR Imaging With Joint Intra-Pulse and Inter-Pulse High-Order Motion Compensation and Sub-Aperture Image Fusion at ULCPI

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.

ISAR Imaging for Nonco-operative Targets Based on Sharpness Criterion Under Low SNR

ISAR Imaging for Nonco-operative Targets Based on Sharpness Criterion Under Low SNR

Fast ISAR imaging method for complex manoeuvring target based on local polynomial transform‐fast chirp Fourier transform

In ISAR imaging, echo signals of complex manoeuvring targets have to be modelled as multi-component cubic phase signals (m-CPS). In this condition, the Doppler diffusion will seriously affect the quality of ISAR imaging. Herein, a complex manoeuvring target imaging method based on local polynomial transform-fast chirp Fourier transform (LPT-FCFT) is proposed. In this method, the instantaneous frequency and the quadratic chirp rate of the echo signal are estimated by local polynomial transformation, then the chirp rate and the amplitude are estimated by fast chirp Fourier transform, and finally the high-resolution ISAR image of the complex manoeuvring target is obtained by CLEAN technology. Compared with the traditional method, the proposed method has the advantages of less computational complexity, clearer imaging results and better anti-noise performance. Simulation results indicate the effectiveness and superiority of the proposed 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.

ISAR imaging and contour feature extraction of space targets

ISAR imaging and contour feature extraction of space targets

An Optimal Imaging Time Interval Selection Technique for Marine Targets ISAR Imaging Based on Sea Dynamic Prior Information

Marine targets are usually involved in remarkably strong maneuvering motion due to sea wave disturbance, which will cause continual change of inverse synthetic aperture radar image projection plane (ISAR IPP). As a result, optimal imaging time interval (OITI) selection is indispensable to obtain well-focused ISAR images. Conventional OITI selection algorithms are entirely driven by echo signal, so strong noise has been always challenging the conventional methods in parameter estimation, and the algorithm accuracy is insufficient. Moreover, the analyses for echo signal in traditional methods cost a considerable number of computational loads, leading to low algorithm efficiency. In this paper, a novel OITI selection algorithm for marine targets is proposed via sea dynamic prior information (SDPI) (such as sea state, ship navigation speed, and wave direction angle) instead of echo signal. In the proposed technique, the coupling mechanism between time-varying 3D rotational motion of marine targets (roll, pitch, and yaw) and SDPI can be inferred integrating with hydrodynamics. Based on this, the effective rotational vectors (ERVs) of marine targets relative to radar line of sight (RLOS) can be deduced from the combination of rotational motion and translational motion. It is worth noting that the ERV is an accurate result with the accommodation of complex SDPI rather than an approximate value obtained from the echo signal. By means of the ERV and maximum contrast criterion, the optimal imaging instant (OII) and optimal imaging duration (OID) can be accurately determined, respectively. Without huge computational complexity, the proposed algorithm provides good robustness and high accuracy. Extensive experiments based on electromagnetic simulated data are provided to demonstrate the effectiveness of the proposed algorithm.

Spatial-variant contrast maximization autofocus algorithm for ISAR imaging of maneuvering targets

Spatial-variant contrast maximization autofocus algorithm for ISAR imaging of maneuvering targets

Moving target imaging in multistatic passive radar

This study presents the concept of multistatic passive images. Theoretical considerations are illustrated by the results obtained by imaging a small general aviation plane using DVB-T signals. These results are compared with simulated images derived from the same scenarios in real-life tests. The results described here show that it is possible to obtain ISAR images of aerial targets using multistatic passive radars based on DVB-T signals. Such images could be next applied for non-cooperative target recognition.

ISAR Imaging And Range-Doppler Processing of Air Targets

ISAR Imaging And Range-Doppler Processing of Air Targets

A Novel Non-Uniform Rotational Motion Estimation and Compensation Method for Maneuvering Targets ISAR Imaging Utilizing Particle Swarm Optimization

Non-uniform rotational motion of maneuvering targets can result in nonlinear migration through range cells (MTRC) and high order phase term, making final inverse synthetic aperture radar image severely defocused. Therefore, a novel non-uniform rotational motion estimation and compensation method is proposed to achieve the elimination of high order phase term and nonlinear MTRC. Under the constant acceleration model, the estimation of rotational motion parameters is first modeled as an unconstrained optimization problem with the image entropy as the cost function. Particle swarm optimization is utilized to search the global optimal solution making use of its simple structure and high efficiency. Then, resampling is performed to transform the non-uniform rotational motion into linear movement and then residual high order phase term is eliminated by constructing the corresponding compensation term. On this condition, first-order Keystone transform can be applied to correct the MTRC. Focused image can finally be obtained by performing traditional Fourier transform along the cross-range dimension. Experimental results on simulated data, electromagnetic data, and real data are presented to verify the effectiveness and robustness of our proposed algorithm.

Research on micro-Doppler feature of spatial target

The micro-Doppler (m-D) effect which is also called micro-motion effect is a kind of physical phenomenon, which is often produced in ISAR imaging of space targets. When the space target has a micro-Doppler effect, it will produce frequency modulation for the radar echo and cause serious interference to ISAR imaging of the target. In this paper, the micro-spin model is modeled, and the echo of micro-spin model scattering point is processed respectively by short-time Fourier transform (STFT), Wigner-Vile Distribution (WVD), and pseudo-Wigner-Vile Distribution (PWV), and the micro-Doppler curve is derived. On this basis, for the space target with spin components, this paper introduces an ISAR imaging algorithm using the micro-Doppler removal based on STFT and proposes an improved algorithm based on rigid body parameter estimation, which can obtain better imaging results.

An Adaptive Dwell Scheduling Algorithm for Digital Array Radar Based on Pulse Interleaving

According to the characteristics of signal processing in Digital Array Radar (DAR), a dwell scheduling algorithm is proposed. Based on the pulse interleaving technique, the dwell scheduling algorithm can achieve the sparse-aperture cognitive ISAR imaging of precision tracking targets simultaneously during implementing searching and tracking tasks, which gets the full exploitation of transmitting, waiting and receiving durations of radar dwells. Simulation results demonstrate that, compared with the conventional dwell scheduling algorithms, the proposed algorithm can improve the scheduling performance of DAR.

High-resolution ISAR imaging of maneuvering targets based on sparse reconstruction

Traditional range-instantaneous Doppler (RID) imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. In this paper, a novel ISAR imaging method of maneuvering targets based on sparse reconstruction is proposed, which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. The proposed method exploits the sparse spatial feature of target scene to characterize the sparsity of the echo signal in its time–frequency domain, constructs the instantaneous Fourier-transform-based dictionary that can reflect the time-varying Doppler frequency and then transforms RID imaging into the problem of sparse reconstruction. After discriminating noise range cells from the range cells containing signal components, noise range cells are used for noise level estimation and signal range cells are used for signal reconstruction. Furthermore, the iteration weighted strategy for ISAR image generation is applied to enhance the signal components and suppress noise. Both simulated and real data experiments are performed to evaluate the proposed method, and the experimental results are presented to demonstrate the superiority of the proposed method over traditional imaging methods.