SPECTRAL ESTIMATION METHODS FOR A JOINT SYSTEM OF THE NON-NOISE-LIKE TARGETS DETECTION AND THE NOISE RADIATING SOURCES LOCALIZATION
Keywords:method, spectral estimation, adaptive lattice filter, resolution-measurement criterion, direction-of-arrival, noise radiating sources, resolution.
Context. For many radars, the autonomous systems of the non-noise-like aerial targets (AT) detection and the noise radiating sources (NRS) localization (direction-of-arrival estimation) may be replaced with a single detection-localization system, which carries out the common operations of the AT-detection and the NRS-localization only once. For such a system, groups of noneigenvalue and eigenvalue decomposition based “super-resolving” spectral estimation (SE) methods are considered to substantiate efficient one for the NRS-localization.
Objective. The comparative analysis efficiency of the SE-methods of different groups by a set of criteria and recommendations on their practical application.
Method. The methods’ efficiency is analyzed analytically, under simulation results and their comparison with new results presented in the open literature. In the simulation, a well-grounded and practically examined software-algorithmic basis of adaptive lattice filters for nonparametric SE-methods implementation is used.
The results. It is shown that the SE-methods of both groups have no restrictions on the antenna array configuration (flat, ring, etc.), including when used in non-equal spaced “sparse” antenna arrays with inter-element distances of more than half radar wavelength. A comparison is made on the resolution (determination of the NRS number) and the NRS-localization (direction-of-arrival estimation) efficiency by methods of different groups when using various antenna arrays. It is shown that the methods of the first group (non-eigenvalue based) in terms of the probability of correct resolution, are almost not inferior to the known and new methods of the second group (eigenvalue ones). Based on the set of criteria and practical application conditions for direction-of-arrival estimation of the noise radiating sources, it is recommended to use the Capon’s minimum variance method if there are limitations on the computational complexity of the method. In the absence of such restrictions, it is advisable to use the SE-bank of methods.
Conclusions. For the practical implementation of a joint system of the non-noise-like aerial target detection and the noise radiating sources localization, a structural-algorithmic basis of adaptive lattice filters is preferred. Using latter, along with the weight vector forming for the target detection, it is possible to implement not only the Capon’s method, but also a SE-bank of methods by combining the squares of absolute values of its original vectors’ components.
Fedinin V. V. Statisticheskij analiz mnogokanal’noj adaptivnoj sistemy s korrelyacionnymi obratnymi svyazyami, Radiotekhnika i elektronika, 1982, No. 8, pp. 120–133.
Atamanskiy D. V. Noise emissions sources direction-finding in the process of their background air threats detection in radars with phased antenna array, Radioelectronics and Communications Systems, 2017, Vol. 60, Issue 7, pp. 303–311. https://doi.org/10.3103/S0735272717070032.
Shirman Ya. D. i dr. Radioelektronnye sistemy. Osnovy postroeniya i teoriya: spravochnik, pod red. Ya. D. Shirmana, Moscow, Radiotekhnika, 2007, 512 p.
Marpl-ml. S. L. Cifrovoj spektral’nyj analiz i ego prilozheniya, per. s angl. Moscow, Mir, 1990, 584 p.
Stoica P., Moses R. Introduction to Spectral Analysis. New Jersey, Prentice Hall, 1997, 319 p.
Nechaev Yu. B., Peshkov I. V., Fortunova N. A. Ocenka granicy Kramera-Rao vypuklyh antennyh reshetok s napravlennymi izluchatelyami dlya radiopelengacii, Vіsnik NTU, 2018, Vol. 75, pp. 16–24.
Ermolaev V. T., Flaksman A. G., Elohin A. V., Kupcov V. V. Metod minimal’nogo mnogochlena dlya ocenki parametrov signalov, prinimaemyh antennoj reshetkoj, Akusticheskij zhurnal, 2018, Vol. 64, No. 1, pp. 78–85. DOI: 10.7868/S0320791918010057.
Shmonin O.A. Obobshchenie sverhrazreshayushchego metoda minimal’nogo mnogochlena dlya pelengacii celej v usloviyah prostranstvenno-okrashennogo shuma i pomekh, Zhurnal radioelektroniki, 2021, № 1, pp. 1–23. https:// doi.org/10.30898/1684-1719.2021.1.3.
Lekhovickij D. I., Atamanskij D. V., Kirillov I. G. Raznovidnosti “sverhrazreshayushchih” analizatorov prostranstvenno-vremennogo spektra sluchajnyh signalov na osnove obelyayushchih adaptivnyh reshetchatyh fil’trov, Antenny, 2000, Vyp. 2 (45), pp. 40–54.
Lekhovytskiy D. I., Shifrin Y. S. Statistical analysis of “superresolving” methods for direction-of-arrival estimation of noise radiation sources under finite size of training sample, Signal Processing, 2013, Vol. 93, Issue 12, pp. 3382–3399. doi.org/10.1016/ j.sigpro.2013.03.008.
Shevchenko M. E., Gorovoj A. V., Balashov V. M., Solov’ev S. N. Osobennosti primeneniya metoda ESPRIT pri razlichnyh konfiguraciyah antennyh reshetok, Voprosy radioelektroniki, 2020, No. 12, pp. 30–37. doi.org/10.21778/2218-5453-2020-12-30-37.
Lagovsky B. A., Samokhin A. B., Shestopalov Y. V. Regression methods of obtaining angular superresolution, URSI Asia-Pacific Radio Science Conference (AP-RASC), conf. proc. Publisher: IEEE conference paper. New Delhi, India, 2019 DOI: 10.23919/URSIAP-RASC.2019.8738539.
Al-Azzo M. F., Azzah T Qaba Estimation of location and separation between acoustic emitting sources: a comparison between classical and modern methods, Conference: 6th International Conference on Natural Language Processing, 2020. DOI:10.5121/csit.2020.100411.
Lemos P. R., Silva L.Е., Flôres H. V., Kunzler J. A. Mathematical analysis and improvement of the maximum spatial eigenfilter for direction of arrival estimation, Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 2021, No. 20(1), pp. 76–91. https:// doi.org/10.1590/2179-10742021v20i1874.
Stoica P., Nehorai A. Mode, maximum likelihood and Cramer-Rao bound: conditional and unconditional results, International Conference on Acoustics, Speech, and Signal Processing, 1990, Vol. 5, pp. 2715–2718. DOI: 10.1109/ICASSP.1990.116186.
Stoica P., Nehorai A. MUSIC, maximum likelihood and Cramer-Rao bound: further results and comparisons, IEEE Trans. ASSP, 1990, No. 38, pp. 2140–2150. DOI: 10.1109/29.61541.
Stoica P., Sharman K. Novel eigenanalysis method for direction estimation, IEE Proc. F (Radar Signal Process, 1990, No. 137. – Р. 19–26. DOI: 10.1049/ip-f-2.1990.0004.
Stoica P., Sharman K. C. Maximum likelihood methods for direction-of-arrival estimation, IEEE Transactions on Acoustics, Speech, and Signal Processing, July 1990, Vol. 38, № 7, pp. 1132–1143. DOI: 10.1109/29.57542.
Takahashi R., Inaba T., Takahashi T., Tasaki H. Digital Monopulse Beamforming for Achieving the CRLB for Angle Accuracy, IEEE Transactions on Aerospace and Electronic Systems, Feb. 2018, Vol. 54, No. 1, pp. 315–323.DOI: 10.1109/TAES.2017.2756519.
Eftekhari A., Tanner J., Thompson A., Toader B., Tyagi H. Sparse non-negative super-resolution – simplified and stabilised, Applied and Computational Harmonic Analysis, 2021, № 50, pp. 216–280. // doi.org/10.1016/j.acha. 2019.08.004
Pal P., Vaidyanathan P. P. Coprime sampling and the music algorithm, Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), 2011, pp. 289–294. DOI: 10.1109/DSP-SPE.2011.5739227.
Jian Li, Stoica P., Zheng-She Liu Comparative study of IQML and MODE direction-of-arrival estimators, IEEE Transactions on Signal Processing, Jan. 1998, Vol. 46, № 1. pp. 149–160. DOI: 10.1109/78.651203.
Kou J., Li M., Jiang C. A robust DOA estimator based on compressive sensing for coprime array in the presence of miscalibrated sensors, Sensors, 2019, № 19, Р. 3538. https:// doi.org/10.3390/s19163538
Lagovsky B. A., Samokhin A. B., Shestopalov Y. V. Creating two-dimensional images of objects with high angular resolution, IEEE Asia-Pacific Conf. on Antennas and Propagation, Conf. Publications, 2018, pp. 114 –115. DOI:10.1109/APCAP.2018.8538220.
Si W., Zeng F., Hou C., Peng Z. A sparse-based off-grid DOA estimation method for coprime arrays, Sensors, 2018, No. 18, Р. 3025. DOI:10.3390/s18093025.
Das A., Zachariah D., Stoica P. Comparison of two hyperparameter-free sparse signal processing methods for direction-of-arrival tracking in the HF97 Ocean Acoustic Experiment, IEEE J. Ocean. Eng., 2018, No. 43, pp. 725–734. DOI:10.1109/JOE.2017.2706100.
Chundi Zheng, Huihui Chen, Aiguo Wang Sparsity-aware noise subspace fitting for DOA estimation, Sensors, 2020, No. 20(1), Р. 81. https://DOI.org/10.3390 /s20010081.
Si W., Peng Z., Hou C., Zeng F. Two-dimensional DOA estimation for three-parallel nested subarrays via sparse representation, Sensors, 2018, No. 18, Р. 1861. DOI:10.33 90 / s18061861.
Zhang X., Jiang T., Li Y. and Zakharov Y. A novel block sparse reconstruction method for DOA estimation with unknown mutual coupling, IEEE Communications Letters, Oct. 2019, Vol. 23, № 10, pp. 1845–1848. DOI: 10.1109/LCOMM.2019.2929384.
Lekhovytskiy D. I. Adaptive lattice filters for systems of space-time processing of non-stationary Gaussian processes, Radioelect. and Communic. Systems, 2018, Vol. 61, No. 11, pp. 477–514. DOI :10.20535/S002134 7018110018.
Gershman A.B. Pseudo-randomly generated estimator banks: a new tool for improving the threshold performance of direction finding, IEEE Trans. Signal Process, May 1998, pp. 1351–1364. DOI: 10.1109/78.668797.
Pal P., Gershman A. B. A grid-less approach to underdetermined direction of arrival estimation via low rank matrix denoising, IEEE Signal Processing Letters, June 2014, Vol. 21, No. 6, pp. 737–741. DOI: 10.1109/LSP. 2014.2314175.
Zhang Y. D., Amin M. G., Himed B. Sparsity-based DOA estimation using co-prime arrays, IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 3967–3971. DOI: 10.1109/ICASSP.2013.6638403.
Yang Z., Xie L., Zhang C. Off-grid direction of arrival estimation using sparse bayesian inference, IEEE Transactions on Signal Processing, Jan. 1, 2013, Vol. 61, pp. 38–43. DOI: 10.1109/TSP.2012.2222378.
Xu X., Wei X., Ye Z. DOA estimation based on sparse signal recovery utilizing weighted l1-norm penalty, IEEE Signal Processing Letters, March 2012, Vol. 19, № 3, pp. 155158. DOI: 10.1109/LSP.2012.2183592.
Stoica P., Babu P. Spice and likes: two hyperparameter-free methods for sparse-parameter estimation, Signal Process, 2012, No. 92, pp. 1580–1590. https:// doi.org/10.1016/j.sigpro.2011.11.010.
Rіabuкha V. P., Semeniaka A. V., Katiushyn Ye. A., Atamanskij D. V. Selection of parameters for band-diagonal regularization of maximum likelihood estimates of Gaussian interference correlation matrices and their inverses, Radioelectronics and Communications Systems, 2021, No. 64(5), pp. 229–237. https://DOI.org/10.20535/s002 1347021050010.
Abramovich Yu. I., Spenser N. K., Gorohov A. Yu. Vydelenie nezavisimyh istochnikov izlucheniya v neekvidistantnyh antennyh reshetkah, Uspekhi sovremennoj radioelektroniki, 2001, No. 12, pp. 3–18.
Lekhovickij D. I., Atamanskij D. V., Dzhus V. V., Mysik F. F. Sravnenie razreshayushchej sposobnosti kombinirovannyh pelengatorov razlichnogo tipa v priemnyh sistemah s neidentichnymi kanalami, Antenny, 2003, No. 12 (79), pp. 9–15.
How to Cite
Copyright (c) 2022 Д. В. Атаманський, В. П. Рябуха, В. М. Карташов, А. В. Семеняка, Л. В. Прокопенко
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
The journal allows the authors to hold the copyright without restrictions and to retain publishing rights without restrictions.
The journal allows readers to read, download, copy, distribute, print, search, or link to the full texts of its articles.
The journal allows to reuse and remixing of its content, in accordance with a Creative Commons license СС BY -SA.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License CC BY-SA that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.