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Proceedings Paper

Multisensor-multitarget bias estimation of asynchronous sensors
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Paper Abstract

This paper provides the exact solution for the bias estimation problem in multiple asynchronous sensors using common targets of opportunity. The target data reported by the sensors are usually not time-coincident or synchronous due to the different sampling times. We consider here the case when the sensors obtain the measurements at the same rate but with a phase difference. Since the bias estimation requires time-coincident target data from different sensors, a novel scheme is used to transform the measurements from the different times of the sensors into pseudomeasurements of the sensor biases with additive noises that are zero-mean, white and with easily calculated covariances. These results allow bias estimation as well as the evaluation of the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases in any scenario. Monte Carlo simulation results show that the new method is statistically efficient, i.e., it meets the CRLB. The use of this technique for scale biases in addition to the usual additive (offset) biases is also presented.

Paper Details

Date Published: 9 August 2004
PDF: 12 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.542272
Show Author Affiliations
Xiangdong Lin, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Thiagalingam Kirubarajan, McMaster Univ. (United States)


Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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