3 September 2008 Impact of signal model on data compression for TDOA/FDOA emitter location
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Abstract
Early work in source location using time-difference-of-arrival/frequency-difference-of-arrival (TDOA/FDOA) focused on locating acoustic sources while later work focused on locating electromagnetic sources. The key difference is the signal model assumptions: WSS Gaussian process is widely used in the acoustic case but is not appropriate in the electromagnetic case. The Fisher information (FI) is fundamentally different for the two scenarios and leads to different distortion metrics for data compression algorithms that seek to maximize the FI for a given data rate. We discuss the philosophical impacts of this relevant to the following question: having collected a single set of data and wanting to do the best "job" for that data, should it matter if the data is viewed as coming from a WSS random process? This work shows that one must be careful when using a random signal model. If one takes the operational rate-distortion view, the goal of compression is to adapt the algorithm to the specific data observed. This is a modern view that contrasts with classical rate-distortion where the distortion measure includes an averaging over the ensemble. We assert that for the operational rate-distortion approach with FI as distortion measure, one should not use a random signal model.
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Mark L. Fowler, Mark L. Fowler, Xi Hu, Xi Hu, } "Impact of signal model on data compression for TDOA/FDOA emitter location", Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 707503 (3 September 2008); doi: 10.1117/12.796199; https://doi.org/10.1117/12.796199
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