{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:19:47Z","timestamp":1760149187219,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T00:00:00Z","timestamp":1689120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenzhen Fundamental Research Program","award":["JCYJ20180 307151430655"],"award-info":[{"award-number":["JCYJ20180 307151430655"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to the limited transmission gain of ubiquitous radar systems, it has become necessary to use a long-time coherent integration method for range-Doppler (RD) analysis. However, when the target exhibits high-speed and high-maneuver capabilities, it introduces challenges, such as range migration (RM), Doppler frequency migration (DFM), and velocity ambiguity (VA) in the RD domain, thus posing significant difficulties in target detection and tracking. Moreover, the presence of VA further complicates the problem. To address these complexities while maintaining integration efficiency, this study proposes a hybrid integration approach. First, methods called Keystone-transform (KT) and matched filtering processing (MFP) are proposed for compensating for range migration (RM) and velocity ambiguity (VA) in Radar Detection (RD) images. The KT approach is employed to compensate for RM, followed by the generation of matched filters with varying ambiguity numbers. Subsequently, MFP enables the production of multiple RD images covering different but contiguous Doppler frequency ranges. These RD images can be compiled into an extended RD (ERD) image that exhibits an expanded Doppler frequency range. Second, an improved particle-filter (IPF) algorithm is raised to perform incoherent integration among ERD images and to achieve track-before-detect (TBD) for a target. In the IPF, the target state vector is augmented with ambiguous numbers, which are estimated via maximum posterior probability estimation. Then, to compensate for the DFM, a line spread model (LSM) is proposed instead of the point spread model (PSM) used in traditional PF. To evaluate the efficacy of the proposed method, a radar simulator is devised, encompassing comprehensive radar signal processing. The findings demonstrate that the proposed approach achieves a harmonious equilibrium between integration efficiency and computational complexity when it comes to detecting and tracking high-speed and high-maneuvering targets with intricate maneuvers. Furthermore, the algorithm\u2019s effectiveness is authenticated by exploiting ubiquitous radar data.<\/jats:p>","DOI":"10.3390\/rs15143507","type":"journal-article","created":{"date-parts":[[2023,7,13]],"date-time":"2023-07-13T01:52:25Z","timestamp":1689213145000},"page":"3507","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Hybrid Integration Method-Based Track-before-Detect for High-Speed and High-Maneuvering Targets in Ubiquitous Radar"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1938-7818","authenticated-orcid":false,"given":"Xiangyu","family":"Peng","sequence":"first","affiliation":[{"name":"School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2783-697X","authenticated-orcid":false,"given":"Qiang","family":"Song","sequence":"additional","affiliation":[{"name":"School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8864-8300","authenticated-orcid":false,"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7967-028X","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wu, Q., Chen, J., Wu, H., Zhang, Y., and Chen, Z. (2019, January 1). Experimental Study on Micro-Doppler Effect and Micro-Motion Characteristics of aerial targets based on holographic staring Radar. Proceedings of the 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Chongqing, China.","DOI":"10.1109\/ITAIC.2019.8785528"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1109\/TAES.2021.3111789","article-title":"Performance Comparison of Planar, Cylindrical, and Polygonalized Phased Arrays for Surveillance and Ubiquitous Radar","volume":"58","author":"Dorsey","year":"2022","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_3","unstructured":"Wirth, W.D. (1995, January 8). Long term coherent integration for a floodlight radar. Proceedings of the International Radar Conference, Alexandria, VA, USA."},{"key":"ref_4","unstructured":"(2017). IEEE Standard for Radar Definitions (Standard No. IEEE Std 686-2017 (Revision of IEEE Std 686-2008))."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4013","DOI":"10.1109\/TSP.2016.2558161","article-title":"Long-Time Coherent Integration for Weak Maneuvering Target Detection and High-Order Motion Parameter Estimation Based on Keystone Transform","volume":"Volume 64","author":"Huang","year":"2016","journal-title":"Proceedings of the IEEE Transactions on Signal Processing"},{"key":"ref_6","unstructured":"Zhang, S.-s., Zeng, T., Long, T., and Yuan, H.-p. (2005, January 9\u201312). Dim target detection based on keystone transform. Proceedings of the IEEE International Radar Conference, Arlington, VA, USA."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Perry, R.P., DiPietro, R.C., and Fante, R.L. (2007, January 17\u201320). Coherent Integration With Range Migration Using Keystone Formatting. Proceedings of the 2007 IEEE Radar Conference, Waltham, MA, USA.","DOI":"10.1109\/RADAR.2007.374333"},{"key":"ref_8","unstructured":"Tian, J., Cui, W., and Wu, S. (2014, January 13\u201318). A Novel Method for Parameter Estimation of Space Moving Targets. Proceedings of the IEEE Geoscience and Remote Sensing Letters, Quebec City, QC, Canada."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1109\/TAES.2011.5751251","article-title":"Radon-Fourier Transform for Radar Target Detection, I: Generalized Doppler Filter Bank","volume":"47","author":"Xu","year":"2011","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2473","DOI":"10.1109\/TAES.2011.6034645","article-title":"Radon-Fourier Transform for Radar Target Detection (II): Blind Speed Sidelobe Suppression","volume":"47","author":"Xu","year":"2011","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1109\/TAES.2012.6178044","article-title":"Radon-Fourier Transform for Radar Target Detection (III): Optimality and Fast Implementations","volume":"48","author":"Yu","year":"2012","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6190","DOI":"10.1109\/TSP.2012.2217137","article-title":"Radar Maneuvering Target Motion Estimation Based on Generalized Radon-Fourier Transform","volume":"60","author":"Xu","year":"2012","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yao, D., Zhang, X., and Sun, Z. (2022). Long-Time Coherent Integration for Maneuvering Target Based on Second-Order Keystone Transform and Lv\u2019s Distribution. Electronics, 11.","DOI":"10.3390\/electronics11131961"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.dsp.2017.07.005","article-title":"Ground moving target motion parameter estimation using Radon modified Lv\u2019s distribution","volume":"69","author":"Yu","year":"2017","journal-title":"Digit. Signal Process."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1109\/TSP.2013.2297682","article-title":"Maneuvering Target Detection via Radon-Fractional Fourier Transform-Based Long-Time Coherent Integration","volume":"62","author":"Chen","year":"2014","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2554","DOI":"10.1109\/TAES.2016.150076","article-title":"Hybrid integration for highly maneuvering radar target detection based on generalized radon-fourier transform","volume":"52","author":"Xu","year":"2016","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2408","DOI":"10.1109\/TAES.2018.2887198","article-title":"Radar Detection of Moderately Fluctuating Target Based on Optimal Hybrid Integration Detector","volume":"55","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1184","DOI":"10.1109\/JSTARS.2020.3037200","article-title":"A Hybrid Integration Method for Moving Target Detection With GNSS-Based Passive Radar","volume":"14","author":"He","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"647","DOI":"10.23919\/JSEE.2020.000040","article-title":"Multiple model efficient particle filter based track-before-detect for maneuvering weak targets","volume":"31","author":"Bao","year":"2020","journal-title":"J. Syst. Eng. Electron."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1338","DOI":"10.23919\/JSEE.2021.000113","article-title":"Bayesian track-before-detect algorithm for nonstationary sea clutter","volume":"32","author":"Xu","year":"2021","journal-title":"J. Syst. Eng. Electron."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1981","DOI":"10.1109\/TAES.2021.3054715","article-title":"Guan, R.; Rosenberg, L. A Bernoulli Track-Before-Detect Filter for Interacting Targets in Maritime Radar","volume":"57","author":"Kim","year":"2021","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lu, X., Wang, Z., Deng, M., Shi, J., He, Z., and Li, H. (2022, January 17). Track-Before-Detect Algorithm for Airborne Radar in Compound Gaussian Clutter with Inverse Gaussian Texture. Proceedings of the 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia.","DOI":"10.1109\/IGARSS46834.2022.9884376"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1109\/LSP.2008.917804","article-title":"Parallelizing the Hough Transform Computation","volume":"15","author":"Satzoda","year":"2008","journal-title":"IEEE Signal Process Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1109\/LGRS.2008.2002574","article-title":"Modified Hough Transform for Searching Radar Detection","volume":"5","author":"Zeng","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"35178","DOI":"10.1109\/ACCESS.2021.3061590","article-title":"Radar Maneuvering Target Motion Parameter Estimation Based on Hough Transform and Polynomial Chirplet Transform","volume":"9","author":"Lin","year":"2021","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2564","DOI":"10.1109\/TAES.2019.2948451","article-title":"Expanding Window Dynamic-Programming-Based Track-Before-Detect With Order Statistics in Weibull Distributed Clutter","volume":"56","author":"Elhoshy","year":"2020","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2608","DOI":"10.1109\/TSP.2013.2251338","article-title":"A Novel Dynamic Programming Algorithm for Track-Before-Detect in Radar Systems","volume":"61","author":"Grossi","year":"2013","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/MAES.2012.6397661","article-title":"Student highlight: Dynamic programming-based track-before-detect approach to multitarget tracking","volume":"27","author":"Yi","year":"2012","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Li, W., Yi, W., Teh, K.C., and Kong, L. (2022). Adaptive Multiframe Detection Algorithm With Range-Doppler-Azimuth Measurements. IEEE Trans. Geosci. Remote. Sens., 60.","DOI":"10.1109\/TGRS.2022.3217128"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4104","DOI":"10.1109\/TVT.2020.2976095","article-title":"Multi-Frame Track-Before-Detect Algorithm for Maneuvering Target Tracking","volume":"69","author":"Yi","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3043","DOI":"10.1109\/TVT.2021.3065665","article-title":"Pseudo-Spectrum Based Track-Before-Detect for Weak Maneuvering Targets in Range-Doppler Plane","volume":"70","author":"Wang","year":"2021","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1109\/LSP.2018.2841507","article-title":"Riemann\u2013Langevin Particle Filtering in Track-Before-Detect","volume":"25","author":"Garcia","year":"2018","journal-title":"IEEE Signal Process Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1109\/TAES.2017.2691958","article-title":"Adaptive Auxiliary Particle Filter for Track-Before-Detect With Multiple Targets","volume":"53","author":"Grajal","year":"2017","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1109\/LSP.2020.3002704","article-title":"A Multi-Target Track-Before-Detect Particle Filter Using Superpositional Data in Non\u2013Gaussian Noise","volume":"27","author":"Ito","year":"2020","journal-title":"IEEE Signal Process Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1109\/TAES.2005.1561899","article-title":"Particle filter track-before-detect application using inequality constraints","volume":"41","author":"Park","year":"2005","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Salmond, D.J., and Birch, H. (2001, January 25\u201327). A particle filter for track-before-detect. Proceedings of the 2001 American Control Conference, Arlington, VA, USA.","DOI":"10.1109\/ACC.2001.946220"},{"key":"ref_37","unstructured":"Rutten, M.G., Gordon, N.J., and Maskell, S. (July, January 28). Efficient particle-based track-before-detect in Rayleigh noise. Proceedings of the 7th Proceeding of the International Conference on Information Fusion, Sweden, Stockholm."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1109\/TAES.2017.2775924","article-title":"Lagrange\u2013Polynomial-Interpolation-Based Keystone Transform for a Passive Radar","volume":"54","author":"Pignol","year":"2018","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3229086","article-title":"A Modified Keystone Transform Matched Filtering Method for Space-Moving Target Detection","volume":"60","author":"Zhan","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1109\/LGRS.2008.2000621","article-title":"Doppler Keystone Transform: An Approach Suitable for Parallel Implementation of SAR Moving Target Imaging","volume":"5","author":"Li","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3504","DOI":"10.1109\/TGRS.2011.2129573","article-title":"Processing the Azimuth-Variant Bistatic SAR Data by Using Monostatic Imaging Algorithms Based on Two-Dimensional Principle of Stationary Phase","volume":"49","author":"Wang","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/TSP.2013.2284479","article-title":"The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing","volume":"62","author":"Mulgrew","year":"2014","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Mochnac, J., Marchevsky, S., and Kocan, P. (2009, January 22). Bayesian filtering techniques: Kalman and extended Kalman filter basics. Proceedings of the 2009 19th International Conference Radioelektronika, Bratislava, Slovakia.","DOI":"10.1109\/RADIOELEK.2009.5158765"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1109\/8.402217","article-title":"New approximations to J\/sub 0\/ and J\/sub 1\/ Bessel functions","volume":"43","author":"Gross","year":"1995","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1109\/LSP.2003.814396","article-title":"Sequential importance sampling filtering for target tracking in image sequences","volume":"10","author":"Bruno","year":"2003","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Douc, R., and Cappe, O. (2005, January 15). Comparison of resampling schemes for particle filtering. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, Zagreb, Croatia.","DOI":"10.1109\/ISPA.2005.195385"},{"key":"ref_47","first-page":"414","article-title":"Adaptive Detection Mode with Threshold Control as a Function of Spatially Sampled Clutter-Level Estimates","volume":"29","author":"Finn","year":"1968","journal-title":"Rca Rev."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/14\/3507\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:11:27Z","timestamp":1760127087000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/14\/3507"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,12]]},"references-count":47,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["rs15143507"],"URL":"https:\/\/doi.org\/10.3390\/rs15143507","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,7,12]]}}}