Abstract
We present an algorithm for fusing data from a constellation of RF sensors detecting cellular emanations with the output of a multi-spectral video tracker to localize and track a target with a specific cell phone. The RF sensors measure the Doppler shift caused by the moving cellular emanation and then Doppler differentials between all sensor pairs are calculated. The multi-spectral video tracker uses a Gaussian mixture model to detect foreground targets and SIFT features to track targets through the video sequence. The data is fused by associating the Doppler differential from the RF sensors with the theoretical Doppler differential computed from the multi-spectral tracker output. The absolute difference and the root-mean-square difference are computed to associate the Doppler differentials from the two sensor systems. Performance of the algorithm was evaluated using synthetically generated datasets of an urban scene with multiple moving vehicles. The presented fusion algorithm correctly associates the cellular emanation with the corresponding video target for low measurement uncertainty and in the presence of favorable motion patterns. For nearly all objects the fusion algorithm has high confidence in associating the emanation with the correct multi-spectral target from the most probable background target.
Highlights
Detection and tracking of moving targets in cluttered urban environments is an important task for local law enforcement and security forces
Radio frequency (RF) communications contain identification information about the transmitting source but lack the ability to spatially localize the target with low uncertainty [1]
We propose two metrics to associate the max Doppler differential (DD) from the RF sensor measurements with the theoretical DD from multi-spectral video tracker output; (1) the absolute difference ∆Ik and (2) the root-mean-square difference RMSDk
Summary
Detection and tracking of moving targets in cluttered urban environments is an important task for local law enforcement and security forces. We present a novel combination of passive sensor data fusion by using a constellation of RF sensors measuring a cellular emanation from a specific phone with a multi-spectral imaging sensor detecting and tracking vehicles in a target rich environment. Neither signal contains enough information to allow a particular vehicle to be uniquely identified as the source of the cellular emanations By fusing these two sources of data we demonstrate that a specific target can confidently be identified and tracked through a sequence of frames. We present results on associating the RF sensors with the corresponding target from the multi-spectral video to localize and track a specific moving target with a cell phone.
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