Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108678
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Title: Slow-time MIMO waveform design using pulse-agile-phase-coding for range ambiguity mitigation
Authors: Chang, S
Yang, F
Liang, Z
Ren, W 
Zhang, H
Liu, Q 
Issue Date: Jul-2023
Source: Remote sensing, July 2023, v. 15, no. 13, 3395
Abstract: This paper proposed a Pulse-Agile-Phase-Coding slow-time MIMO (PAPC-st-MIMO) waveform, where the phase-coded signal is utilized as the intra-pulse modulation of the slow-time MIMO waveform. Firstly, the signal model of the proposed waveform is derived. To improve the orthogonality of the phase-coded waveform sets, a novel hybrid evolutionary algorithm based on Cyclic Algorithm New (CAN) is proposed. After the optimization process of the phase-coded waveform sets, the signal processing method of the PAPC-st-MIMO waveform is derived. Finally, the effectiveness of the proposed method is verified with a simulation experiment. The mitigation ratio of the near-range detection waveform can achieve −30 dB, while the long-range detection waveform can achieve −35 dB. This approach ensures waveform orthogonality while enabling the slow-time MIMO waveform to achieve distance selectivity. By conducting joint pulse-Doppler processing across multiple range segments, range ambiguity can be suppressed, increasing the system’s Pulse Repetition Frequency (PRF) without introducing ambiguity.
Keywords: MIMO radar range ambiguity mitigation
MIMO radar waveform design
Pulse agile phase-coding
Slow-time MIMO radar
Publisher: MDPI AG
Journal: Remote sensing 
EISSN: 2072-4292
DOI: 10.3390/rs15133395
Rights: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Chang S, Yang F, Liang Z, Ren W, Zhang H, Liu Q. Slow-Time MIMO Waveform Design Using Pulse-Agile-Phase-Coding for Range Ambiguity Mitigation. Remote Sensing. 2023; 15(13):3395 is available at https://doi.org/10.3390/rs15133395.
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