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When tracking multiple targets using radar sensors, weak targets are often difficult to observe in the presence of strong targets.
The method can take full advantage of radar resources and obtain images for multiple targets using much less pulses than conventional RD method.
Optimal kinematic rules are obtained by minimizing the covariances of parallel extended Kalman filters that track multiple targets using only target-informative sensors.
By applying group sparsity-based signal reconstruction methods in the ambiguity domain, therefore, it is possible to simultaneously utilize the signal energy in all available bistatic links for estimating the acceleration of multiple targets, using the process detailed as follows.
In this paper, a novel target acquisition and localisation algorithm (TALA) is introduced that offers a capability for detecting and localising multiple targets using the intermittent "signals-of-opportunity" (e.g. acoustic impulses or radio frequency transmissions) they generate.
In this paper, we study the problem of multi-robot cooperative target tracking, where a team of mobile robots cooperatively localize themselves and track (multiple) targets using their onboard sensor measurements as well as target stochastic kinematic information, and which is hence termed cooperative localization and target tracking (CLATT).
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In [14], the authors tracked multiple flying targets using a Multiple Hypothesis Tracker (MHT).
This paper proposes an approach for tracking multiple articulated targets using a combined data association and evolving population particle filter.
The method renders a better performance in range sidelobe suppression for the detection of multiple moving targets using Golay complementary waveforms than the existing Binominal Design algorithm.
It will be very challenging to apply our method for inferring multiple drug targets using experimental double knock-out screens as e.g. of the synthetic lethal project of eSGA [ 55].
Figure 3 Trajectory of multiple targets (a) using proposed method (red/blue), (b) using baseline method (magenta/black) and (c) using Non-MCMC baseline method (green/blue), the JPDA PF proposed in [37, 38].
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