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In multisensor systems, the measurements reported by local sensors are usually not time aligned or synchronous due to different data rates. A novel algorithm, based on Kalman filter combined with pseudomeasurement and equivalent bias, is proposed to solve a general bias estimate problem in asynchronous sensors systems. The pseudomeasurement equation of sensor biases is obtained by linearizing the...
The main drawback of probability hypothesis density (PHD) filter is that it canpsilat identify the trajectories of the different targets. Data association for PHD filter based on multiple hypotheses tracking (MHT) is presented to solve the problem. The track-oriented MHT is used to perform data association on the output of PHD filter. An adaptive Kalman filter based on ldquocurrentrdquo statistic...
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