3 September 1993 Model-based joint detection/estimation approach for multisensor data fusion
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Abstract
A nonlinear adaptive detector/estimator is introduced for single and multiple sensor data processing. The problem of target detection from returns of monostatic sensor(s) is formulated as a nonlinear joint detection/estimation (JDE) problem on the unknown parameters in the signal return. The unknown parameters involve the presence of the target, its range, and azimuth. The problems of detecting the target and estimating its parameters are considered jointly. A bank of spatially and temporally localized nonlinear filters is used to estimate the a posteriori likelihood of the existence of the target in a given space-time resolution cell. Within a given cell, the localized filters are used to produce refined spatial estimates of the target parameters. A decision logic is used to decide on the existence of a target within any given resolution cell based on the a posteriori estimates reduced from the likelihood functions. The inherent spatial and temporal referencing in this approach is used for automatic referencing required when multiple sensor data is fused together.
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Thomas W. Hilands, Stelios C.A. Thomopoulos, "Model-based joint detection/estimation approach for multisensor data fusion", Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); doi: 10.1117/12.154978; https://doi.org/10.1117/12.154978
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KEYWORDS
Sensors

Target detection

Error analysis

Signal to noise ratio

Silicon

Doppler effect

Nonlinear filtering

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