Paper
30 January 2003 Integer optimization methods for non-MSE data compression for emitter location
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Abstract
The location of an emitter is estimated by intercepting its signal and sharing the data among several platforms to measure the time-difference-of-arrival (TDOA) and the frequency-difference-of-arrival (FDOA). A common compression approach is to use a rate-distortion criterion where distortion is taken to be the mean-square error (MSE) between the original and compressed versions of the signal. However, we show that this MSE-only approach is inappropriate for TDOA/FDOA estimation and then define a more appropriate, non-MSE distortion measure. This measure is based on the fact that in addition to the dependence on MSE, the TDOA accuracy also depends inversely on the signal's RMS (or Gabor) bandwidth and the FDOA accuracy also depends inversely on the signal's RMS (or Gabor) duration. The form of this new measure must be optimized under the constraint of a specified budget on the total number of bits available for coding. We show that this optimization requires a selection of DFT cells to retain that must be jointly chosen with an appropriate allocation of bits to the selected DFT cells. This joint selection/allocation is a challenging integer optimization problem that still has not been solved. However, we consider three possible sub-optimal approaches and compare their performance.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark L. Fowler and Mo Chen "Integer optimization methods for non-MSE data compression for emitter location", Proc. SPIE 4793, Mathematics of Data/Image Coding, Compression, and Encryption V, with Applications, (30 January 2003); https://doi.org/10.1117/12.453520
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Cited by 7 scholarly publications.
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KEYWORDS
Signal to noise ratio

Distortion

Computer programming

Data compression

Quantization

Atrial fibrillation

Signal processing

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