Improved navigation-based motion compensation for LFMCW synthetic aperture radar imaging

Saeedi, Jamal; Alavi, Seyed Mohammad

doi:10.1007/s11760-015-0755-7

Cited by 6 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where ( ) is the signal amplitude and defines the pulse length with a rect function, 0 is the frequency at the beginning of the chirp, is chirp rate, and 0 is the starting phase which can usually be neglected A power amplifier increases the signal power to a specified level in the transmission chain. An antenna propagates the amplified signal to the target area [14][15][16]. A very small portion of the transmit signal is reflected back to the radar.…”

Section: Basic Principle Of Sar Signal Modellingmentioning

confidence: 99%

A New Hybrid Method for Synthetic Aperture Radar Deceptive Jamming

Saeedi¹

2019

JMICRO

Self Cite

View full text Add to dashboard Cite

Based on the synthetic aperture radar (SAR) geometric model, a novel, and fast algorithm of large scene deceptive jamming against different SAR systems is proposed. First, a template deceptive image is transformed into the time domain signal using inverse image formation algorithm. Then, the transformed signal is convolved with enemy's received SAR signal in order to cope with electronic countercountermeasures (ECCM) techniques. Finally, the generated jamming signal is transmitted to enemy's SAR system for deceptive purpose. Specifically, we have proposed a hybrid method for SAR jamming, which uses a digital radio frequency memory (DRFM) system incorporating with SAR raw data simulation module. The experimental results for the proposed deceptive jammer demonstrate its ability to deceive SAR system.

show abstract

Section: Basic Principle Of Sar Signal Modellingmentioning

confidence: 99%

A New Hybrid Method for Synthetic Aperture Radar Deceptive Jamming

Saeedi¹

2019

JMICRO

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, it is not feasible to equip a UAV with a highly accurate sensor due to the physical space and payload capacity limitations of UAVs. Thus even after applying MoCo, only coarsely focused images are generated [5,6]. Furthermore, with the improvement of range resolution, the unknown residual motion errors (RMEs) inevitably exceed a range cell and severely impair the image quality loss of the radiometric or geometric resolution [7].…”

Section: Introductionmentioning

confidence: 99%

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

Wang

Xiang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

The combination of synthetic aperture radar (SAR) with unmanned aerial vehicles (UAVs) is attractive for acquiring high-resolution images without the restrictions of time and weather. However, because UAVs are lightweight and small in size, the UAV SAR system is very sensitive to turbulence, resulting in serious trajectory deviations and remaining residual motion errors (RMEs), such as residual range cell migration (RCM) and aperture phase errors (APEs). In this paper, a novel motion compensation (MoCo) strategy is developed based on the symmetric triangle linear frequency modulated continuous wave (STLFMCW) signal. The STLFMCW signal model is first presented, which reveals the relevance between the positive-negative frequency modulations and motion errors. The residual RCMs and relative phase errors are estimated directly through the phase differential interferometry of up-ramp and down-ramp chirp signals, instead of the traditional approach of relying on the range-shift gradient of adjacent range profiles. The proposed approach is independent of conventional prominent point processing (PPP) and calculates the range deviation to avoid the accumulation of errors, thereby achieving high precision and efficiency. Experiments based on simulated and measured data sets validate the proposed approach.

show abstract

“…However, low‐rate motion measurements systems provide only coarse MC, e.g. removal of partial phase error and the residual range cell migration [2, 3].…”

Section: Introductionmentioning

confidence: 99%

Improved phase curvature autofocus for stripmap synthetic aperture radar imaging

Saeedi

2020

IET signal process.

Self Cite

View full text Add to dashboard Cite

Based on the theory of phase curvature autofocus (PCA) on stripmap synthetic aperture radar (SAR), an improved algorithm for increasing the accuracy of phase error compensation is presented in this study. PCA method was proposed to extend the phase gradient autofocus method for SAR systems in stripmap mode. The main problems concerned with the traditional PCA algorithm are related to selecting candidates in the image for phase error estimation, windowing, estimation procedure, and range shift due to the phase error. In this study, the modification of traditional PCA algorithm has been performed in different steps including the following: improving range‐compressed data, prominent points extraction, adaptive windowing, weighted maximum likelihood for phase error estimation, improving phase error result, range shift compensation, and determining the condition to end the iterations. Real data experiments demonstrate the success of the proposed autofocus method, which is applied to the stretched‐based pulsed mode SAR data set in the absence of highly accurate inertial navigation units.

show abstract

Improved navigation-based motion compensation for LFMCW synthetic aperture radar imaging

Cited by 6 publications

References 12 publications

A New Hybrid Method for Synthetic Aperture Radar Deceptive Jamming

A New Hybrid Method for Synthetic Aperture Radar Deceptive Jamming

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

Improved phase curvature autofocus for stripmap synthetic aperture radar imaging

Contact Info

Product

Resources

About