Paper
13 September 2004 Range precision of direct-detection laser radar systems
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Abstract
A direct detection time-of-flight ladar simulator has been developed to synthesize noisy realizations of true range for the purpose of testing the performance of target recognition algorithms. The simulator can model either peak report or peak report above a threshold using computationally efficient analytic models. In addition, the simulator can also model arbitrary detection logic by direct simulation for cases where analytic models do not exist. Two types of range estimates can occur, local and global. Local errors represent error about the true target range and are described by a Gaussian distribution whose width is given by the Cramer-Rao lower bound. Global errors represent errors that occur because the noise, in one or more bins within the range search interval, is stronger than the target echo. These errors are called "anomalies" and, for peak detection logic, are uniformly distributed over the range search interval. In this paper, the probability density function (PDF) that accounts for both local and global errors is derived. The PDF is a function of signal-to-noise ratio (SNR), range search interval (RSI), and level of speckle diversity. The signal synthesizer uses these PDFs to synthesize the range errors much faster than via direct simulation. Simple approximations to the anomaly probability are derived for high SNRs. The predicted range precision is compared to the results of Monte Carlo simulations of the noisy received signals.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven E. Johnson, Terry L. Nichols, Philip Gatt, and T.J. Klausutis "Range precision of direct-detection laser radar systems", Proc. SPIE 5412, Laser Radar Technology and Applications IX, (13 September 2004); https://doi.org/10.1117/12.553991
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CITATIONS
Cited by 11 scholarly publications and 2 patents.
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KEYWORDS
Signal to noise ratio

LIDAR

Logic

Speckle

Data modeling

Interference (communication)

Monte Carlo methods

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