Target geolocation in Gotcha data using cross-channel interferometry

Murthy, Vinay; Uysal, Faruk; Scarborough, Steven

doi:10.1109/radar.2014.6875547

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Spatio-temporal Connectivity1

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Cited by 3 publications

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“…4. The updated Z in (2) can can be used for subsequent processing as described in [6] for target detection and geolocation. We refer to this method as the three channel ATI (Modified ATI/DPCA).…”

Section: (B)mentioning

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: (B)mentioning

confidence: 99%

“…11. For each such A i , its present velocity V r along the range direction is known [5], [6] and hence V r (T i+1 − T i ) represents its possible projected location P along the range direction in the next frame. Construct a box of uncertainty U around P that represents the location uncertainty at P .…”

Section: Spatio-temporal Connectivitymentioning

confidence: 99%