NDLI: Altitude measurement of low-angle target in complex terrain for very high-frequency radar

Content Provider	IET Digital Library
Author	Zheng, Yisong Chen, Baixiao
Abstract	For low-angle targets, the performance of altitude measurement is affected by multipath phenomenon. Especially, for complex terrain case, the main problem is due to the fact that the multipath signal is perturbed by irregular reflector, which leads to the mismatch of the steering vector, and thus degrades the performance of or even fails the existing methods. To deal with this problem, the authors propose a new perturbational multipath signal model, where perturbation caused by complex terrain is considered as the gain and phase errors of the steering vector of the multipath signal. With the spatial sparsity of the incident signals, the sparse Bayesian learning technique is adopted to estimate the perturbation and direction of arrival (DOA) iteratively. The computer simulation results show that their algorithm is able to estimate the effect of perturbation with high precision and to enhance the DOA accuracy compared with existing algorithms. Furthermore, real data analysis validates the efficiency of altitude measurement in practice. Finally, the proposed perturbational multipath signal model is also applicable to other situations where complex multipath phenomenon is not negligible.
Starting Page	967
Ending Page	973
Page Count	7
ISSN	17518784
Volume Number	9
e-ISSN	17518792
Issue Number	Issue 8, Oct (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/9/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2014.0544
Journal	IET Radar, Sonar & Navigation
Publisher Date	2015-06-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Altitude Measurement Bayes Method Complex Terrain Case Data Analysis Data Handling Technique Direction of Arrival Direction of Arrival Estimation DOA Accuracy Electrical Engineering Computing Gain Error Height Measurement Incident Signal Knowledge Engineering Technique Learning in AI Low-angle Targets Multipath Channel Perturbation Technique Perturbational Multipath Signal Model Phase Error Radar Computing Radar Equipment Radar Signal Processing Real Data Analysis Signal Processing And Detection Sparse Bayesian Learning Technique Spatial Sparsity Spatial Variables Measurement Statistics Steering Vector System And Application Very High-frequency Radar VHF Radar
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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