APPLICATION OF THE SPATIAL FILTERING METHOD USING A SET OF MATRIX FILTERS -PROJECTORS TO DETERMINE THE COMPOSITION OF A GROUP TARGET WITHIN A SINGLE PULSE VOLUME OF A RADAR STATION
DOI:
https://doi.org/10.17721/2519-481X/2025/89-02Keywords:
групова ціль, система високого розрізнення, імпульсний об’ємAbstract
This paper addresses one of the critical challenges in modern radar systems – the determination of the composition of group concentrated targets (GCTs) within the radar’s impulse volume. The authors analyze advanced high‑resolution methods that surpass the Rayleigh limit, focusing on alternative spectral analysis algorithms (such as MUSIC and Capon) and projection‑based approaches. While spectral methods are limited by signal correlation and computational complexity, projection methods offer a more practical pathway to implementation.
The study proposes a spatial signal processing algorithm based on matrix projector filters (MPFs), enabling quasi‑optimal resolution without the need to compute the inverse correlation matrix. The methodology is grounded in functional analysis and employs the least‑squares criterion, ensuring adaptability under uncertain signal parameters. A structural scheme of the system is developed, incorporating multiple MPFs tuned to different target models. For the case of two targets within the impulse volume, the system utilizes a pair of projectors—one matched to a single target and the other to a dual‑target configuration. The decision on the number of targets is made by comparing the outputs of these channels against a predefined threshold, effectively implementing a procedure close to optimal resolution.
Monte Carlo simulations confirm the efficiency of the proposed approach. Results demonstrate that at a signal‑to‑noise ratio of 16–20 dB, the high‑resolution system based on dual MPFs achieves reliable separation of group targets, providing resolution twice as effective as the Rayleigh criterion.
In conclusion, the paper contributes significantly to the development of super‑resolution radar systems, presenting a technically feasible algorithm capable of operating under conditions of high signal correlation. The findings hold substantial tactical importance for target detection and classification in contemporary radar applications. Keywords: geographic information system, geospatial data, geospatial support, ArcGIS, LiDAR, terrain change mapping, remote sensing, raster georeferencing, topographic map updating.
References
1. Robert A. Monzingo; Randy L. Haupt; Thomas W. Miller "Introduction to Adaptive Arrays" (2nd Edition), 2011. – 543 р. DOI: https://doi.org/10.1049/SBEW046E
2. C. Schuessler, M. Hoffmann, and M. Vossiek, "Super-Resolution Radar Imaging with Sparse Arrays Using a Deep Neural Network" IEEE Journal of Microwaves, vol. 3, no. 1, pp. 45–56, 2023. DOI: DOI: https://arxiv.org/pdf/2306.09839
3. S. Yang, Y. Zhao, X. Tuo, et al., "Real Aperture Radar Angular Super-Resolution Imaging Using Modified Smoothed L0 Norm" Remote Sensing, vol. 16, no. 2, pp. 312, 2024. https://doi.org/10.3390/rs16010012
4. B.-S. Kim, Y. Jin, J. Lee, and S. Kim, "FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area" Sensors, vol. 22, no. 3, pp. 1456, 2022. https://doi.org/10.3390/s22031202
5. Raymond J. Weber; Yikun Huang "Analysis for Capon and MUSIC DOA estimation algorithms" 2009 IEEE Antennas and Propagation Society International Symposium, June 2009 DOI: https://doi.org/10.1109/APS.2009.5171460.
6. Bondarenko B.F., Prokofev V.P. "Prymenenye metodov funktsyonalnoho analyza dlia reshenyia zadachy synteza system prostranstvennoi obrabotky // Radyoelektronyka. – 1982. – Т. 25, № 3. – С. 15-23.
7. Bondarenko B.F., Sashchuk Y.Y., Tymchuk V.Iu. "Predelnoe kachestvo obnaruzhenyia y razreshenyia syhnalov v obnaruzhyteliakh na osnove sohlasovannikh proektorov" // Visti vyshchykh uchbovykh zakladiv. Radioelektronika, №48(3) – 2005. – С.24-33,. DOI: https://doi.org/10.20535/S0021347005030039
8. C. Radhakrishna Rao. "Linear Statistical Inference and its Applications" 2nd Edition, Wiley, New York, 1973. – 625р. DOI: https://doi.org/10.1002/9780470316436
