Modified Chirp Scaling Algorithm for Ultra-High Resolution Spaceborne-SAR

Abstract The hyperbolic range equation model (HREM) and equivalent squint range model (ESRM) are applied in traditional chirp scaling algorithm (CSA). However, these range models cannot describe the satellite range history in the high-resolution case accurately because of the long azimuth integration time. The non-negligible phase error caused by this will lead the targets distort. In this paper, a modified chirp scaling algorithm (MCSA) is proposed by introducing a novel high-precision range model. A more accurate signal spectrum is calculated through it. Then, the modified chirp scaling factor, range compression filter, range cell migration correction (RCMC) filter and azimuth compression filter can be derived based on this signal spectrum, and the focused target obtained at last. Finally, the experimental results, to validate the proposed algorithm, adopted by the sliding spotlight synthetic aperture radar (SAR) simulation are provided.

Download Full-text

A Novel Motion Compensation Scheme for Airborne Very High Resolution SAR

Remote Sensing ◽

10.3390/rs13142729 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2729

Author(s):

Zhen Chen ◽

Zhimin Zhang ◽

Yashi Zhou ◽

Pei Wang ◽

Jinsong Qiu

Keyword(s):

High Resolution ◽

Motion Compensation ◽

Phase Error ◽

Measurement Unit ◽

Motion Error ◽

Invariant Approximation ◽

Range Cell ◽

Range Cell Migration ◽

Synthetic Aperture Radars ◽

Very High

Due to the atmospheric turbulence, the motion trajectory of airborne very high resolution (VHR) synthetic aperture radars (SARs) is inevitably affected, which introduces range-variant range cell migration (RCM) and aperture-dependent azimuth phase error (APE). Both types of errors consequently result in defocused images, as residual range- and aperture-dependent motion errors are significant in VHR-SAR images. Nevertheless, little work has been devoted to the range-variant RCM auto-correction and aperture-dependent APE auto-correction. In this paper, a precise motion compensation (MoCo) scheme for airborne VHR-SAR is studied. In the proposed scheme, the motion error is obtained from inertial measurement unit and SAR data, and compensated for with respect to both range and aperture. The proposed MoCo scheme compensates for the motion error without space-invariant approximation. Simulations and experimental data from an airborne 3.6 GHz bandwidth SAR are employed to demonstrate the validity and effectiveness of the proposed MoCo scheme.

Download Full-text

Presenting a New Technique for Multi-Target Tracking in Inverse Synthetic Aperture Radar based on PHD Filter in the Presence of Clutters

Frequenz ◽

10.1515/freq-2017-0172 ◽

2018 ◽

Vol 72 (7-8) ◽

pp. 391-399 ◽

Cited By ~ 1

Author(s):

Hamid Dehghani ◽

Navid Daryasafar

Keyword(s):

Cell Migration ◽

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Moving Targets ◽

Inverse Synthetic Aperture Radar ◽

Probability Hypothesis Density ◽

Implementation Phase ◽

Range Cell ◽

Range Cell Migration ◽

Aperture Radar

Abstract Using Probability Hypothesis Density (PHD) filtering, a novel approach is proposed in this paper for simultaneous tracking of multiple moving targets in received data by Inverse Synthetic Aperture Radar (ISAR) system. Since PHD filtering approach is implemented successively in prediction and update steps, its performance quality will obviously be higher in “Spotlight” imaging mode than in “Stripmap”. Thus, its application to Spotlight mode is generally more logical. The idea to integrate tracking capability into ISAR system processor is to sort radar received data to correct Range Cell Migration (RCM) prior to tracking operations. Clearly, Range Cell Migration Compensation (RCMC) approach is different from this approach in image formation process, in terms of their implementation phase. However, they are implemented in a similar way. As simulation results reveal, applying Range Cell Migration Compensation to the raw data received by ISAR before tracking operation, results in high quality tracking of moving targets.

Download Full-text

An ASIC implementation of range cell migration compensation algorithm for synthetic aperture radar signal processing

VLSI Signal Processing, VIII ◽

10.1109/vlsisp.1995.527485 ◽

2002 ◽

Author(s):

Ji-Heub Kim ◽

Lee-Sup Kim

Keyword(s):

Signal Processing ◽

Cell Migration ◽

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Radar Signal ◽

Radar Signal Processing ◽

Compensation Algorithm ◽

Range Cell ◽

Range Cell Migration ◽

Aperture Radar

Download Full-text

An Improved Generalized Chirp Scaling Algorithm Based on Lagrange Inversion Theorem for High-Resolution Low Frequency Synthetic Aperture Radar Imaging

Remote Sensing ◽

10.3390/rs11161874 ◽

2019 ◽

Vol 11 (16) ◽

pp. 1874 ◽

Cited By ~ 1

Author(s):

Xing Chen ◽

Tianzhu Yi ◽

Feng He ◽

Zhihua He ◽

Zhen Dong

Keyword(s):

High Resolution ◽

Stationary Phase ◽

Low Frequency ◽

Synthetic Aperture ◽

Phase Coupling ◽

Lagrange Inversion ◽

Inversion Theorem ◽

Coupling Phase ◽

Large Bandwidth ◽

Chirp Scaling Algorithm

The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is generally accepted as an attractive solution to focus SAR systems with low frequency, large bandwidth and wide beam bandwidth. However, as the bandwidth and/or beamwidth increase, the serious phase coupling limits the performance of the current GCSA and degrades the imaging quality. The degradation is mainly caused by two reasons: the residual high-order coupling phase and the non-negligible error introduced by the linear approximation of stationary phase point using the principle of stationary phase (POSP). According to the characteristics of a high-resolution low frequency SAR signal, this paper firstly presents a principle to determine the required order of range frequency. After compensating for the range-independent coupling phase above 3rd order, an improved GCSA based on Lagrange inversion theorem is analytically derived. The Lagrange inversion enables the high-order range-dependent coupling phase to be accurately compensated. Imaging results of P- and L-band SAR data demonstrate the excellent performance of the proposed algorithm compared to the existing GCSA. The image quality and focusing depth in range dimension are greatly improved. The improved method provides the possibility to efficiently process high-resolution low frequency SAR data with wide swath.

Download Full-text

A Fast High-Resolution Imaging Algorithm for Helicopter-Borne Rotating Array SAR Based on 2-D Chirp-Z Transform

Remote Sensing ◽

10.3390/rs11141669 ◽

2019 ◽

Vol 11 (14) ◽

pp. 1669 ◽

Cited By ~ 1

Author(s):

Qin ◽

Li ◽

Tang ◽

Zeng ◽

Li ◽

...

Keyword(s):

High Resolution ◽

Taylor Series Expansion ◽

High Resolution Imaging ◽

Imaging Algorithm ◽

Range Cell ◽

Distortion Effect ◽

Resolution Imaging ◽

Range Cell Migration ◽

Azimuth Resolution ◽

Space Variant

In view of the azimuth resolution of the helicopter-borne rotating array synthetic aperture radar (RoASAR) depending on the azimuth reconstruction angle and the sector distortion caused by the azimuth Deramp processing, this paper proposes an efficient helicopter-borne RoASAR high-resolution imaging algorithm based on two-dimensional (2-D) chirp-z transform (CZT). First, the high-order Taylor series expansion is performed on the slant range, and the accurate 2-D spectral expression of the point target is obtained by using the method of series reversion (MSR). Based on that, the space-variant characteristics of the range cell migration (RCM) terms are analyzed. After that, the space-variant RCM and the sector distortion effect caused by the azimuth Deramp processing are removed by using efficient 2-D CZT, thereby increasing the azimuth reconstruction angle and improving the azimuth resolution. The proposed algorithm is efficient without the interpolation operation, and it is easy to implement in real-time. Finally, the simulations are provided to verify the effectiveness of the proposed algorithm.

Download Full-text