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Multi-Sensor Fusion Algorithms
For sensing and control applications, it is often desirable to utilize multiple sensors to improve the fidelity of perception by increasing the observation opportunities. APS applies innovative mathematical techniques to the process of associating observations over space and time to improve scene awareness.
In multi-static radar and active sonar applications, the use of statistics based probabilistic data association in conjunction with target state space estimation has been employed to produce robust surveillance capabilities with low cost sensors. In passive sensing applications, models of target signature generation are utilized to predict observation features of targets from spatially diverse sensor positions to enable robust signal association and tracking parameter estimation.
Examples of multi-sensor fusion algorithms and applications developed at APS include:
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Multi-static active acoustic swimmer detection systems |
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Multi-sensor passive non-acoustic sensing of hydrodynamic signature associated with swimmers and aquatic animals |
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Multi-sensor noise monitoring for artillery range events |
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Automated multi-static urban surveillance using distributed RF sensors |
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