Distributed Detection With Mismatched Sensors

Stelios C.A. Thomopoulos; Nickens N. Okello

doi:10.1117/12.948937

5 January 1989 Distributed Detection With Mismatched Sensors

Stelios C.A. Thomopoulos, Nickens N. Okello

Proceedings Volume 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation; (1989) https://doi.org/10.1117/12.948937
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

We consider the problem of distributed detection based on a system of two sensors that transmit raw data to a central processor (fusion center) responsible for making the final decision when the region jointly covered by the two sensors contains sub-regions that are blind spots to each of the sensors. Preliminary assumptions include a known geometry of the visible and blind spots, symmetric coverage of the region by the two sensors and uniform distribution of a target in the coverage region. We formulate and compare three detection schemes. In the first scheme, the a-priori information on the coverage factor along with the data from both sensors are used directly to detect the presence of the target with no attempt to estimate its position first. In the second scheme, a preliminary estimate of the target position is used to deternime whether the target is visible by both sensors, one only, or none. Once a decision is taken on which sensor data to use, a likelihood ratio test is implemented for target detection. This scheme therefore estimates the probable target location and then proceeds to detect it. In the third scheme, estimates of the most likely position of the target, if the target were present, are incorporated in the detection model, and the presence of the target is detected by using a likelihood ratio test. Numerical results for the three schemes are presented for the Gaussian channel.

Citation Download Citation

Stelios C.A. Thomopoulos and Nickens N. Okello "Distributed Detection With Mismatched Sensors", Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); https://doi.org/10.1117/12.948937

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KEYWORDS

Sensors

Target detection

Fourier transforms

Sensor fusion

Holmium

Data fusion

Signal to noise ratio

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