Abstract:
This paper deals with target classification by using both feature data and kinematic measurements. The problem is tackled by multihypothesis sequential testing with embed...Show MoreMetadata
Abstract:
This paper deals with target classification by using both feature data and kinematic measurements. The problem is tackled by multihypothesis sequential testing with embedded target tracking. We implement an Armitage sequential test for nonmaneuvering and maneuvering targets. Both (centralized and distributed) fusion architectures are used for the embedded tracking. The contributions of the kinematic measurements to classification are analyzed, and classification performance improvement is shown analytically for a special case. Numerical results are provided to demonstrate the performance of our algorithms.
Published in: IEEE Transactions on Aerospace and Electronic Systems ( Volume: 54, Issue: 1, February 2018)