Blind phase calibration for along-track interferometry: application to Gotcha data set

Uysal, Faruk; Murthy, Vinay; Scarborough, Steven

doi:10.1117/12.2058259

Cited by 2 publications

(3 citation statements)

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“…The details of the algorithms involved in each step in Fig. 1 are explained in [5]- [7]. In the next phase, higher level algorithms along with other a-priori information such as proximity to known roads and temporal data sequence are used to geolocate the true moving targets.…”

Section: Panoramic Processingmentioning

confidence: 99%

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Target geolocation in Gotcha data using panoramic processing

Pillai

Scarborough

2015

2015 IEEE Radar Conference (RadarCon)

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Any signal processing methodology when blindly applied to realistic data sets generates a significant number of false targets along with estimates for the true moving targets. In an effort to isolate the true movers from the false targets, a new approach exploiting spatio-temporal connectivity in addition to signal processing algorithms involving imaging and interferometry is proposed here to geolocate the movers in a measured data set.

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Section: Panoramic Processingmentioning

confidence: 99%

“…Fig. 1 is achieved using a blind phase calibration method described in [7]. As an alternate processing methodology, a modified ATI/Interferogram method that makes use of traditional DPCA concepts (along the lines in [3]) is developed below.…”

Section: (B)mentioning

confidence: 99%

Target geolocation in Gotcha data using panoramic processing

Pillai

Scarborough

2015

2015 IEEE Radar Conference (RadarCon)

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“…However, the filter is only suited for ocean applications. In Shen et al [3] and Uysal et al [12], pixels in a series of images need to be sequenced to select the medium value, and then all the medium value pixels constitute the stationary clutter image. However, the algorithm increases the computational complexity significantly.…”

Section: Introductionmentioning

confidence: 99%

Moving Target Indication for Dual-Channel Circular SAR/GMTI Systems

Wang

et al. 2019

Sensors

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In a dual-channel circular synthetic aperture radar (CSAR) and ground moving target indication (GMTI) system, the antenna baseline is not parallel with the flight path due to a yaw angle. The angle causes a varying group-phase shift between the dual-channel signals and therefore degrades the correlation between the image pair. Therefore, the group-phase shift needs to be removed before channel equalization. To resolve the problem, the interferometric phase term was deduced and analyzed based on the geometry of a dual-channel CSAR system. Then, the varying phase term with respect to the Doppler frequency and the varying group-phase shift over the range were compensated for in the channel registration. Furthermore, blind channel equalization, including two-dimensional calibration and amplitude equalization, was applied to eliminate the amplitude and residual phase differences between the channels. Finally, the amplitude image obtained using a displaced phase center antenna (DPCA) was multiplied by the phase image obtained with along-track interferometry (ATI) to detect moving targets. The experimental results verified the effectiveness of the method for both uniform and non-uniform clutter suppression.

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Blind phase calibration for along-track interferometry: application to Gotcha data set

Cited by 2 publications

References 1 publication

Target geolocation in Gotcha data using panoramic processing

Target geolocation in Gotcha data using panoramic processing

Moving Target Indication for Dual-Channel Circular SAR/GMTI Systems

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