Maximum likelihood estimation applied to quantum-limited optical position-sensing

Computer Science – Performance

Scientific paper

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Maximum Likelihood Estimates, Optical Communication, Position Errors, Position Sensing, Star Trackers, Infrared Detectors, Signal To Noise Ratios

Scientific paper

Star-tracking systems, optical communication systems, and infrared tracking systems are examples in which the measurement and correction of alignment errors between the optical source and receiver must be made. In this paper, a new position estimator is developed that retains accuracy even under poor SNR conditions. This estimator is derived using an estimation theoretic approach to the problem of tracking a quasi-stationary object given photoevent data in a continuously distributed detector. A maximum likelihood position estimator is derived via application of the expectation-maximization (EM) algorithm. Simulation results are given to show that under low SNR conditions, the estimator performance is superior to that of the commonly used centroid estimator.

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