Paper
21 August 2001 Sensor bias estimation and compensation for improved track correlation
Gregory A. Watson, Theodore R. Rice
Author Affiliations +
Abstract
The integration of multiple sensors for the purpose of forming a single integrated air picture has been intensely investigated in recent years. Assuming no sensor biases and minimal communication latencies, the ideal picture can be formed when all the sensor information is communicated to each network node. The state vector for each target at every node should be identical under this ideal condition. However, this is not the situation when sensor bias is considered since it has an adverse effect on the tracking performance by increasing the estimation error. A method to account for the location, measurement, and attitude biases of the sensors must be employed to provide more accurate state estimates of the target. This paper will present a method for estimating sensor measurement bias in a multi- target environment. The output of the bias estimation process will be employed to compensate the sensor measurements for the tracking of highly maneuvering aircraft. Utilizing the common tracks of multiple sensors, a comparison between compensated and uncompensated techniques will be provided through simulation.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory A. Watson and Theodore R. Rice "Sensor bias estimation and compensation for improved track correlation", Proc. SPIE 4365, Acquisition, Tracking, and Pointing XV, (21 August 2001); https://doi.org/10.1117/12.438039
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Error analysis

Monte Carlo methods

Detection and tracking algorithms

Environmental sensing

Composites

Statistical analysis

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