Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing

This paper researches adaptive stagger-block-lattice-filtering (SBLF), phase-code pulse compression (PC), and stagger PRI (pulse repetition interval) technologies, which can be used in an MTI radar. First, we deduce the compatibility between the MTI filtering and PC, especially the placement order of both. When the MTI filter is a transversal filter, the overall performance is independent of the placement order; however, when the MTI filtering is adaptive filtering, e.g., real-time weight calculating and filtering, the overall performance is much dependent on their placement order. The deduction and simulation verify that a much better signal-clutter-ratio improvement is reached when the PC is placed behind the adaptive filtering. The high speed and small radar-cross-section of a target compel an MTI radar to be upgraded with stagger PRI, PC transmission, and adaptive filtering. In such a case, only arithmetic computation largely restricts clutter suppression performance in complex environments. Our experiments of years prove the necessity of incorporating AI into MTI processor, i.e., utilizing abundant prior knowledge. Then, we describe the basic knowledge for the multi-technology processor: adaptive filtering reasoning center, performance behaviors of two filtering modes, detection threshold set-up, target-terrace identification, and utilization of stagger PRI. Thereupon, five heuristic strategies for the intelligent operation are proposed: 1) non-clutter block decision and threshold set-up, 2) PC target-terrace identifications, 3) SBLF coefficient estimation, 4) Establishment of clutter-map, 5) Utilization of multiple stagger PRIs. In order to verify the effectiveness of the intelligent operations, we make many experiments using computer and the basic architecture parameters are based on a ship-borne radar; the generated clutters reflect land, sea, and weather returns, and the selected targets reflect weak, high-speed aircraft returns. In the strong homogeneous and severe heterogeneous clutters, this processor demonstrates maximized performance to acquire the weak targets.

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Publication Details

Journal
International Journal of Information and Communication Sciences
Published
2025-11-28
DOI
https://doi.org/10.11648/j.ijics.20251003.11
Primary Topic
Radar Systems and Signal Processing
Type
article
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article

Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing

Xubao Zhang
International Journal of Information and Communication Sciences
Radar Systems and Signal Processing
article

Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing

Xubao Zhang
article en

Abstract

This paper researches adaptive stagger-block-lattice-filtering (SBLF), phase-code pulse compression (PC), and stagger PRI (pulse repetition interval) technologies, which can be used in an MTI radar. First, we deduce the compatibility between the MTI filtering and PC, especially the placement order of both. When the MTI filter is a transversal filter, the overall performance is independent of the placement order; however, when the MTI filtering is adaptive filtering, e.g., real-time weight calculating and filtering, the overall performance is much dependent on their placement order. The deduction and simulation verify that a much better signal-clutter-ratio improvement is reached when the PC is placed behind the adaptive filtering. The high speed and small radar-cross-section of a target compel an MTI radar to be upgraded with stagger PRI, PC transmission, and adaptive filtering. In such a case, only arithmetic computation largely restricts clutter suppression performance in complex environments. Our experiments of years prove the necessity of incorporating AI into MTI processor, i.e., utilizing abundant prior knowledge. Then, we describe the basic knowledge for the multi-technology processor: adaptive filtering reasoning center, performance behaviors of two filtering modes, detection threshold set-up, target-terrace identification, and utilization of stagger PRI. Thereupon, five heuristic strategies for the intelligent operation are proposed: 1) non-clutter block decision and threshold set-up, 2) PC target-terrace identifications, 3) SBLF coefficient estimation, 4) Establishment of clutter-map, 5) Utilization of multiple stagger PRIs. In order to verify the effectiveness of the intelligent operations, we make many experiments using computer and the basic architecture parameters are based on a ship-borne radar; the generated clutters reflect land, sea, and weather returns, and the selected targets reflect weak, high-speed aircraft returns. In the strong homogeneous and severe heterogeneous clutters, this processor demonstrates maximized performance to acquire the weak targets.

International Journal of Information and Communication SciencesVol. 10(3)
Xi'an University of Science and Technology (CN)
Openalex Percentile: Top 51%
Radar Systems and Signal Processing
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