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- W2610124360 abstract "MIMO sonar systems can offer great capabilities for area surveillance especially in very shallow water with heavy cluttered environment. We present here a MIMO simulator which can compute synthetic raw data for any transmitter/receiver pair in multipath and cluttered environment. Synthetic moving targets such as boats or AUVs can also be introduced into the environment. For the harbour surveillance problem we are interested in tracking all moving objects in a particular area. So far the tracking filter of choice for multistatic systems has been the MHT (Multiple Hypothesis Tracker). The reason behind this choice is its capability to propagate track identities at each iteration. The MHT is an extension of a mono object tracker to a multi object problem and therefore suffers from a number of drawbacks: the number of targets should be known and the birth or death of new tracks are based on heuristics. A fine ad hoc parameter tuning is then required and there is a lack of adaptivity in this process. To overcome those restrictions we will be using the HISP (Hypothesised multi-object filter for Independent Stochastic Population) filter recently developed by [1]. The HISP filter relies on a generalisation of the concept of point process that integrates a representation of distinguishability. As a consequence, this filter deals directly with the multi-object estimation problem, while maintaining track identities through time without using heuristics. While filters track the objects after processing in the digital domain, we show as well in this paper that we can adapt acoustical time reversal techniques to track an underwater target directly with the MIMO system. We will show that the proposed modified DORT technique matches the prediction / data update steps of a tracking filter." @default.
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- W2610124360 date "2014-06-01" @default.
- W2610124360 modified "2023-09-23" @default.
- W2610124360 title "Tracking underwater objects using large MIMO sonar systems" @default.
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