Data-Driven Motion Compensation Techniques for Noncooperative ISAR Imaging

2020

Sensors

Due to self-motion and sea waves, moving ships are typically defocused in synthetic aperture radar (SAR) images. To focus non-cooperative targets, the inverse SAR (ISAR) technique is commonly used with motion compensation. The hybrid SAR/ISAR approach allows a long coherent processing interval (CPI), in which SAR targets are processed with ISAR processing, and exploits the advantages of both SAR and ISAR to generate well-focused images of moving targets. In this paper, based on hybrid SAR/ISAR processing, we propose an improved rank-one phase estimation method (IROPE). By using an iterative two-step convergence approach in the IROPE, the proposed method achieves accurate phase error, maintains robustness to noise and performs well in estimating various phase errors. The performance of the proposed method is analyzed by comparing it with other focusing algorithms in terms of processing simulated data and real complex image data acquired by Gaofen-3 (GF-3) in spotlight mode. The results demonstrate the effectiveness of the proposed method.

Section: The Whole Process Of the Refocusing Methodsmentioning

confidence: 99%

A Hybrid SAR/ISAR Approach for Refocusing Maritime Moving Targets with the GF-3 SAR Satellite

Yan

2020

Sensors

“…2 Rocket Force University of Engineering, 710025 Xi'an, China. 3 School of Electronics and Communication Engineering, Sun Yat-sen University, Xingangxi Road, 510275 Guangzhou, China.…”

Section: Acknowledgementsmentioning

confidence: 99%

Noise-Robust Range Alignment Method for Inverse Synthetic Aperture Radar Based on Aperture Segmentation and Average Range Profile Correlation

Yang²,

2020

Preprint

Range alignment is an essential procedure in the translation motion compensation of inverse synthetic aperture radar imaging. Global optimization or maximum-correlation-based algorithms have been used to realize range alignment. However, it is still challenging to achieve range alignment in low signal-to-noise ratio scenarios, which are common in inverse synthetic aperture radar imaging. In this paper, a novelanti-noise range alignment approach is proposed. In this new method, the target motion is modelled as a uniformly accelerated motion during a short sub-aperture time. Minimum entropy optimization is implemented to estimate the motion parameters in each sub-aperture. These estimated parameters can be used to align the profiles of the current sub-aperture. Once the range profiles of eachsub-aperture are aligned, the non-coherent accumulation gain is obtained by averaging all profiles in each sub-aperture, which can be used as valuable information. The accumulation and correlation method is applied to align the average range profiles of each sub-aperture because the former step focuses mainly on alignment within the sub-apertures. Experimental results based on simulated and real measured data demonstrate the effectiveness of the proposed algorithm in low signal-to-noise ratio scenarios.

“…This section firstly presents conventional ISAR imaging geometry and dechirped signal model [6]- [8]. And then, the characteristics of 2-D time-variant phase errors are also analyzed.…”

Section: Imaging Geometry and Signal Modelmentioning

confidence: 99%

“…According to (6), the phase of the first exponential term on the right-hand side can be rewritten as…”

Section: A Isar Imaging Geometry and Dechirped Signal Modelmentioning

confidence: 99%

Improved Intra-Pulse Modulation Phase Calibration Algorithm With Accelerated Entropy Minimization Optimization

et al. 2019

IEEE Access

Intra-pulse modulation phase calibration is necessary in inverse synthetic aperture radar (ISAR) imaging of high-speed targets. Traditional intra-pulse phase error compensation strategies rarely handle the high-order and slow-time-variant phase components induced during the coherent processing interval. In this paper, a novel intra-pulse modulation phase calibration with a two-dimensional (2-D) parametric phase model is proposed. It models the intra-pulse phase errors as a 2-D time-variant polynomial with accommodation of both fast-time and slow-time modulation. Entropy minimization of high-resolution range profiles (HRRPs) is developed to retrieve the phase error parameters. Improved coordinate descent optimization solver is established by Levenberg-Marquardt (LM) algorithm in order to find the global optimum of entropy efficiently. Comparative experiments using both simulated and real measured data are performed to demonstrate the enhancements of the proposed algorithm. INDEX TERMS Entropy minimization, intra-pulse modulation, inverse synthetic aperture radar (ISAR), phase error compensation.