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

Xubao Zhang

doi:doi:10.11648/j.ijics.20251003.11

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

Xubao Zhang^*

Published in International Journal of Information and Communication Sciences (Volume 10, Issue 3)

Received: 10 October 2025 Accepted: 22 October 2025 Published: 28 November 2025

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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.

Published in	International Journal of Information and Communication Sciences (Volume 10, Issue 3)
DOI	10.11648/j.ijics.20251003.11
Page(s)	57-71
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Adaptive Filtering, Artificial Intelligence, Lattice Filter, Pulse Compression, Stagger PRI, MTI

References

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[3]	Wenxu Zhang, Shudi Ma, Qiuying Du. Optimization of Adaptive MTI Filter. Int. J. Communications, Network and System Sciences. 2017, 10, 206-217.
[4]	Dingqing Lu. Simulation, Veriﬁcation of Pulse Doppler Radar Systems Application Note. USA. 2010. Available from: www.agilent.com/find/radar (accessed 19 July 2025).
[5]	Jie Song, Wei Xiong, Xiaolong Chen, Yuan Lu. Experimental Study of Maritime Moving Target Detection Using Hitchhiking Bistatic Radar Note. Remote Sensing. 2022, 14, 3611. https://doi.org/10.3390/rs14153611
[6]	Simon Haykin, Adaptive filter theory. Fifth Edition. London, UK: Pearson Education Limited, Edinburgh Gate, 2014, pp. 150-208.
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[13]	Raviraj S. Adve, Michael C. Wicks, Todd B. Hale, Paul Antonik. Ground Moving Target Indication Using Knowledge Based Space Time Adaptive Processing. Record of the IEEE 2000 International Radar Conference, VA, USA, 2000; pp. 735-740.
[14]	Chris Allen. Radar Pulse Compression 2004. Available from: https://www.mathworks.com›help›signal (accessed 19 July 2025).
[15]	Greg C, Jon R. Efficient Exhaustive Search for Optimal-Peak-Sidelobe Binary Codes. IEEE TRANS. on AES. 2005, 41(1), 302-308.
[16]	Xubao Zhang. Lattice Predictors for Stagger-Period Sequence: their Theory and Application. Science PG Journal of Electrical and Electronic Engineering. 2022, 10(5), 184-198.
[17]	Xubao Zhang. New Methods of Simulating Radar Clutter Return Arrays. EJECE, European Journal of Engineering and Computer Science. 2023, 7(6), 46-57.
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[21]	Capt. H. Subramaniam, Shipborne radar and ARPA. Third edition. Mumbai India: VIJAYA PUBLICATIONS; 2001, pp. 1-78.

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APA Style

Zhang, X. (2025). Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. International Journal of Information and Communication Sciences, 10(3), 57-71. https://doi.org/10.11648/j.ijics.20251003.11

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ACS Style

Zhang, X. Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. Int. J. Inf. Commun. Sci. 2025, 10(3), 57-71. doi: 10.11648/j.ijics.20251003.11

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AMA Style

Zhang X. Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. Int J Inf Commun Sci. 2025;10(3):57-71. doi: 10.11648/j.ijics.20251003.11

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@article{10.11648/j.ijics.20251003.11,
  author = {Xubao Zhang},
  title = {Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing},
  journal = {International Journal of Information and Communication Sciences},
  volume = {10},
  number = {3},
  pages = {57-71},
  doi = {10.11648/j.ijics.20251003.11},
  url = {https://doi.org/10.11648/j.ijics.20251003.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20251003.11},
  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.},
 year = {2025}
}

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TY  - JOUR
T1  - Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing
AU  - Xubao Zhang
Y1  - 2025/11/28
PY  - 2025
N1  - https://doi.org/10.11648/j.ijics.20251003.11
DO  - 10.11648/j.ijics.20251003.11
T2  - International Journal of Information and Communication Sciences
JF  - International Journal of Information and Communication Sciences
JO  - International Journal of Information and Communication Sciences
SP  - 57
EP  - 71
PB  - Science Publishing Group
SN  - 2575-1719
UR  - https://doi.org/10.11648/j.ijics.20251003.11
AB  - 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.
VL  - 10
IS  - 3
ER  -

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Author Information

Xubao Zhang

Department of EE, Xi’an University of Electronic Science and Technology, Xi’an, China; Research and Development, Unitron Sonova, Kitchener, Canada

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http://orcid.org/0009-0008-9096-2647

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Zhang, X. (2025). Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. International Journal of Information and Communication Sciences, 10(3), 57-71. https://doi.org/10.11648/j.ijics.20251003.11

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ACS Style

Zhang, X. Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. Int. J. Inf. Commun. Sci. 2025, 10(3), 57-71. doi: 10.11648/j.ijics.20251003.11

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AMA Style

Zhang X. Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing. Int J Inf Commun Sci. 2025;10(3):57-71. doi: 10.11648/j.ijics.20251003.11

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@article{10.11648/j.ijics.20251003.11,
  author = {Xubao Zhang},
  title = {Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing},
  journal = {International Journal of Information and Communication Sciences},
  volume = {10},
  number = {3},
  pages = {57-71},
  doi = {10.11648/j.ijics.20251003.11},
  url = {https://doi.org/10.11648/j.ijics.20251003.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20251003.11},
  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.},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Compatibility of Adaptive Filtering and Pulse Compression, and Knowledge-aided Multi-technology MTI Processing
AU  - Xubao Zhang
Y1  - 2025/11/28
PY  - 2025
N1  - https://doi.org/10.11648/j.ijics.20251003.11
DO  - 10.11648/j.ijics.20251003.11
T2  - International Journal of Information and Communication Sciences
JF  - International Journal of Information and Communication Sciences
JO  - International Journal of Information and Communication Sciences
SP  - 57
EP  - 71
PB  - Science Publishing Group
SN  - 2575-1719
UR  - https://doi.org/10.11648/j.ijics.20251003.11
AB  - 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.
VL  - 10
IS  - 3
ER  -

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