Mingjie Jia , Bang Huang , Abdul Basit , Wen-Qin Wang
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引用次数: 0
Abstract
Different from conventional phased array (PA) and multiple-input-multiple-output (MIMO) radars, frequency diverse array (FDA) experiences the additional Doppler-spread and Doppler walk phenomena caused by the coupling among frequency increment, velocity, and acceleration. In this paper, we thoroughly investigate the coherent integration issue for detecting an FDA-based maneuvering target, consisting of range migration, Doppler-spread and Doppler walk phenomena. To address these challenges, the paper presents a novel algorithm. Specifically, we first introduce a new pulse sampling interval into the FDA-based signals to propose the resampling-keystone transform (RKT) stage, which effectively correct range migration and Doppler-spread. After the inter-channel compensation and integration of the resampled signals, the Lv's distribution (LVD) stage is applied to achieve the intra-channel coherent integration of target energy. The proposed algorithm is applicable for both single-target and multi-target scenarios. Finally, several simulation results demonstrate the potential of the proposed algorithm for improved detection performance for FDA radar. Additionally, the results indicate the underlying limitations of frequency increment and acceleration, which is caused by the coupling among frequency increment, acceleration, and quadratic slow time.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,