{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T01:09:08Z","timestamp":1771636148168,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T00:00:00Z","timestamp":1688515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61871400"],"award-info":[{"award-number":["61871400"]}]},{"name":"National Natural Science Foundation of China","award":["62273356"],"award-info":[{"award-number":["62273356"]}]},{"name":"National Natural Science Foundation of China","award":["BK20211227"],"award-info":[{"award-number":["BK20211227"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["61871400"],"award-info":[{"award-number":["61871400"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["62273356"],"award-info":[{"award-number":["62273356"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["BK20211227"],"award-info":[{"award-number":["BK20211227"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In the scenario of device-free localization under multiple effects, the accuracy of localization based on compressed sensing theory is severely affected. Most existing localization techniques directly ignore multiple path effects. However, it is not practical to ignore the multiple path effect due to its high signal strength, which can provide localization information. In this paper, we formulate the sensing matrix optimization problem in compressed sensing for device-free localization scenarios based on multiple reflections. To solve this problem, we model it as a constrained combinatorial optimization problem and propose a hybrid meta-heuristic algorithm. First, smart reflection surfaces and virtual node models are used to construct the desired communication links. Second, we iteratively improve the properties of the measurement matrix by using K-means clustering to obtain reasonable thresholds, and use a meta-heuristic algorithm to optimize the sensing matrix. Finally, the simulation results show that the proposed method efficiently optimizes the sensing matrix and achieves fast and high-precision localization while conserving communication resources.<\/jats:p>","DOI":"10.3390\/e25071025","type":"journal-article","created":{"date-parts":[[2023,7,6]],"date-time":"2023-07-06T00:34:30Z","timestamp":1688603670000},"page":"1025","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Meta-Heuristic Device-Free Localization Algorithm under Multiple Path Effect"],"prefix":"10.3390","volume":"25","author":[{"given":"Huajing","family":"Li","sequence":"first","affiliation":[{"name":"College of Communications Engineering, PLA Army Engineering University, Nanjing 210007, China"}]},{"given":"Ning","family":"Li","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, PLA Army Engineering University, Nanjing 210007, China"}]},{"given":"Yan","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, PLA Army Engineering University, Nanjing 210007, China"}]},{"given":"Hao","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, PLA Army Engineering University, Nanjing 210007, China"}]},{"given":"Binghan","family":"Lei","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, PLA Army Engineering University, Nanjing 210007, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1109\/JIOT.2019.2950174","article-title":"TagSort: Accurate Relative Localization Exploring RFID Phase Spectrum Matching for Internet of Things","volume":"7","author":"Lai","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhao, J., Frumkin, N., Konrad, J., and Ishwar, P. (2018, January 18\u201322). Privacy-Preserving Indoor Localization via Active Scene Illumination. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Salt Lake City, UT, USA.","DOI":"10.1109\/CVPRW.2018.00208"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Juan, G.-I., Zeadally, S., and Contreras-Castillo, J. (2018). Sensor technologies for intelligent transportation systems. Sensors, 18.","DOI":"10.3390\/s18041212"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"13812","DOI":"10.1109\/TVT.2020.3027957","article-title":"PRSRTI: A Novel Device-Free Localization Method Using Phase Response Shift Based Radio Tomography Imaging","volume":"69","author":"Ma","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1109\/TVT.2022.3208070","article-title":"RAPP: A Radio Tomography Localization Method Characterized by Performance Parameterization in Rapid-Moving RFID System","volume":"72","author":"Ma","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TMC.2016.2567396","article-title":"E-HIPA: An energy-efficient framework for high-precision multi-target-adaptive device-free localization","volume":"16","author":"Wang","year":"2016","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2550","DOI":"10.1109\/TMC.2018.2812746","article-title":"Low human-effort, device-free localization with fine-grained subcarrier information","volume":"17","author":"Wang","year":"2018","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Talampas, M.C.R., and Low, K.S. (2014, January 21\u201324). Geometry-based algorithms for device-free localization with wireless sensor networks. Proceedings of the 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Singapore.","DOI":"10.1109\/ISSNIP.2014.6827625"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Liu, D., Liu, Z., and Song, Z. (2020, January 22\u201324). LDA-Based CSI Amplitude Fingerprinting for Device-free Localization. Proceedings of the 2020 Chinese Control and Decision Conference (CCDC), Hefei, China.","DOI":"10.1109\/CCDC49329.2020.9164348"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Sood, P., Dubey, A., Chiu, C.Y., and Murch, R. (2020, January 5\u201310). Demonstrating Device-free Localization based on Radio Tomographic Imaging. Proceedings of the 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, Montreal, QC, Canada.","DOI":"10.1109\/IEEECONF35879.2020.9330243"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"7067","DOI":"10.1109\/JSEN.2020.3040280","article-title":"Localization of Multiple RF Sources Based on Bayesian Compressive Sensing Using a Limited Number of UAVs with Airborne RSS Sensor","volume":"21","author":"Jiang","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","article-title":"Compressed sensing","volume":"52","author":"Donoho","year":"2006","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MSP.2007.914731","article-title":"An Introduction to Compressive Sampling","volume":"25","author":"Candes","year":"2008","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5695","DOI":"10.1109\/TSP.2007.900760","article-title":"Optimized Projections for Compressed Sensing","volume":"55","author":"Elad","year":"2007","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_15","first-page":"128","article-title":"Deterministic constructions of compressed sensing matrices based on optimal codebooks and codes","volume":"343","author":"Gang","year":"2019","journal-title":"Appl. Math. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"21710","DOI":"10.1109\/ACCESS.2018.2824329","article-title":"Deterministic Construction of Measurement Matrices Based on Bose Balanced Incomplete Block Designs","volume":"6","author":"Haiqiang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1109\/LSP.2018.2809693","article-title":"Compressive Sensing Matrix Design for Fast Encoding and Decoding via Sparse FFT","volume":"25","author":"Hsieh","year":"2018","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_18","first-page":"2497","article-title":"Deterministic Bipolar Compressed Sensing Matrices from Binary Sequence Family","volume":"14","author":"Lu","year":"2020","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2448","DOI":"10.1108\/EC-09-2015-0269","article-title":"A novel compressive sensing method based on SVD sparse random measurement matrix in wireless sensor network","volume":"33","author":"Ma","year":"2016","journal-title":"Eng. Comput."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1109\/TMC.2011.216","article-title":"Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing","volume":"11","author":"Feng","year":"2012","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Li, X., Chen, J., Tan, W., Wen, Y., and Zhang, R. (2019, January 20\u201323). Sensing Dictionary Optimization Method for Target Localization in Sensor Networks. Proceedings of the 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Dalian, China.","DOI":"10.1109\/ICSPCC46631.2019.8960710"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1109\/MCOM.001.1900107","article-title":"Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network","volume":"58","author":"Wu","year":"2020","journal-title":"IEEE Commun. Mag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7399","DOI":"10.1109\/JSEN.2022.3154591","article-title":"A Training-Free Multipath Enhancement (TFME-RTI) Method for Device-Free Multi-Target Localization","volume":"22","author":"Zhang","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_24","first-page":"129","article-title":"Atomic decomposition by basis pursuit","volume":"20","author":"Chen","year":"1998","journal-title":"SIAM Rev."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4655","DOI":"10.1109\/TIT.2007.909108","article-title":"Signal Recovery from Random Measurements Via Orthogonal Matching Pursuit","volume":"53","author":"Tropp","year":"2007","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2346","DOI":"10.1109\/TSP.2007.914345","article-title":"Bayesian Compressive Sensing","volume":"56","author":"Ji","year":"2008","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3320","DOI":"10.1109\/TIT.2003.820031","article-title":"Sparse representations in unions of bases","volume":"49","author":"Gribonval","year":"2003","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Holland, J.H. (1992). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT Press.","DOI":"10.7551\/mitpress\/1090.001.0001"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cheng, Y., and Peng, W. (2020, January 7\u201311). Codebook-based Phase Adjustment for IRS-aided Communication Via Time-Coding Modulation. Proceedings of the GLOBECOM 2020\u20142020 IEEE Global Communications Conference, Taipei, Taiwan.","DOI":"10.1109\/GLOBECOM42002.2020.9348171"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1109\/JSAC.2020.3000835","article-title":"Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning","volume":"38","author":"Huang","year":"2020","journal-title":"IEEE J. Sel. 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