초록 ▼

A multi-sensor system adaptively utilizes communications or data bus facilities for multi-sensor signal fusion. For each source of sensor signals, a local signal processor compares each signal against a pre-determined set of hypotheses, and generates a ranking value corresponding to each hypothesis.

A multi-sensor system adaptively utilizes communications or data bus facilities for multi-sensor signal fusion. For each source of sensor signals, a local signal processor compares each signal against a pre-determined set of hypotheses, and generates a ranking value corresponding to each hypothesis. An adaptive interface unit then selects the highest ranking values and transmits them, together with an identification of the hypothesis to which they correspond, through the multi-sensor system communication network or data bus, to the system signal processor. The system signal processor then multiplies the ranking from the various sensors, or adds their logarithms and selects the hypothesis whose product (or logarithmic sum) is greatest. This provides for transmission of the highest ranking hypothesis, or of a selection of hypotheses, to identify the target detected by multiple snsors.

대표청구항 ▼

In a multi-sensor system which has a plurality of sensors which receive target echo return signals from a tracked target, and a plurality of local signal processors, each being electrically connected to, and receiving said target echo return signals from one of said sensor systems and producing a pl

In a multi-sensor system which has a plurality of sensors which receive target echo return signals from a tracked target, and a plurality of local signal processors, each being electrically connected to, and receiving said target echo return signals from one of said sensor systems and producing a plurality of hypothesis identifications with probability rankings of said hypothesis identifications for said target by comparing said target echo return signals with expected characteristics of target identifies, wherein the improvement comprises: a signal fusion processor which is programmed to produce a highest ranking hypothesis identification by composing probability sums for each hypothesis identification by adding logarithms of probability rankings of like hypothesis identifications from each of the local signal processors to create a set of probability sums, with one probability sum for each hypothesis identification, and outputting the hypothesis identification with the highest probability sum as the highest ranking hypothesis identification; and a means for identifying said tracked target, said identifying means identifying said tracked target as having the hypothesis identification with the highest probability sum produced by said signal fusion processor.