Short-Time Velocity Identification and Coherent-Like Detection of Ultra-High Speed Targets
journal contributionposted on 2018-08-17, 15:20 authored by Jun Chen, Fei Wang, Jianjiang Zhou, Ling Li, Danny Crookes, Huiyu Zhou
Finding a balance between observation duration and detection rates is the ultimate goal of the detection of ultra high speed targets. However, short observation durations, both across range unit (ARU) and Doppler frequency migration (DFM), may severely limit the detection performance of ultra high speed targets. Although traditional coherent integration methods can efficiently accumulate signal energy to produce a high signal to noise ratio (SNR) measurement, they often need to search for unknown motion parameters. This search is timeconsuming and unacceptable for real-time detection of ultra high speed targets. In this paper, a coherent-like detection method is designed based on the finite-dimension theory of Wigner matrices along with velocity identification. The proposed method can efficiently integrate signal energy without rendering motion parameters. We use the distribution and mean of the eigenvalues of the constructed matrix, i.e. an additive Wigner matrix, to identify velocities and detect ultra high speed targets, respectively. Simulation results validate the theoretical derivation, superiority and operability of the proposed method.
CitationIEEE Transactions on Signal Processing, 2018, 66(18)
Author affiliation/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Informatics
- AM (Accepted Manuscript)