{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T10:46:47Z","timestamp":1777805207465,"version":"3.51.4"},"reference-count":38,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the complexity of background and diversity of small targets, robust detection of infrared small targets for the trajectory correction fuze has become a challenge. To solve this problem, different from the traditional method, a state-of-the-art detection method based on density-distance space is proposed to apply to the trajectory correction fuze. First, parameters of the infrared image sensor on the fuze are calculated to set the boundary limitations for the target detection method. Second, the density-distance space method is proposed to detect the candidate targets. Finally, the adaptive pixel growth (APG) algorithm is used to suppress the clutter so as to detect the real targets. Three experiments, including equivalent detection, simulation and hardware-in-loop, were implemented to verify the effectiveness of this method. Results illustrated that the infrared image sensor on the fuze has a stable field of view under rotation of the projectile, and could clearly observe the infrared small target. The proposed method has superior anti-noise, different size target detection, multi-target detection and various clutter suppression capability. Compared with six novel algorithms, our algorithm shows a perfect detection performance and acceptable time consumption.<\/jats:p>","DOI":"10.3390\/s21134522","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T12:03:27Z","timestamp":1625141007000},"page":"4522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Infrared Small Target Detection Method with Trajectory Correction Fuze Based on Infrared Image Sensor"],"prefix":"10.3390","volume":"21","author":[{"given":"Cong","family":"Zhang","sequence":"first","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongguang","family":"Li","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiashuo","family":"Qi","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingtao","family":"Liu","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Deng, Z., Shen, Q., Deng, Z., and Cheng, J. (2019). Real-Time Estimation for Roll Angle of Spinning Projectile Based on Phase-Locked Loop on Signals from Single-Axis Magnetometer. Sensors, 19.","DOI":"10.3390\/s19040839"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.ast.2014.12.027","article-title":"Robust gain-scheduled autopilot design for spin-stabilized projectiles with a course-correction fuze","volume":"42","author":"Theodoulis","year":"2015","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"He, C., Xiong, D., Zhang, Q., and Liao, M. (2019). Parallel Connected Generative Adversarial Network with Quadratic Operation for SAR Image Generation and Application for Classification. Sensors, 19.","DOI":"10.3390\/s19040871"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yue, R., Wang, H., Jin, T., Gao, Y., Sun, X., Yan, T., Zang, J., Yin, K., and Wang, S. (2021). Image Motion Measurement and Image Restoration System Based on an Inertial Reference Laser. Sensors, 21.","DOI":"10.3390\/s21103309"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, R., Li, D., and Fan, J. (2019). Correction Strategy of Mortars with Trajectory Correction Fuze Based on Image Sensor. Sensors, 19.","DOI":"10.3390\/s19051211"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.2514\/1.53584","article-title":"Guidance and Control of a Projectile with Reduced Sensor and Actuator Requirements","volume":"34","author":"Fresconi","year":"2011","journal-title":"J. Guid. Control. Dyn."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"94994","DOI":"10.1109\/ACCESS.2019.2928718","article-title":"Dynamic Response Analysis for a Terminal Guided Projectile with a Trajectory Correction Fuze","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhang, C., and Li, D. (2020). Mechanical and Electronic Video Stabilization Strategy of Mortars with Trajectory Correction Fuze Based on Infrared Image Sensor. Sensors, 20.","DOI":"10.3390\/s20092461"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Uzair, M., Brinkworth, R., and Finn, A. (2021). Detecting Small Size and Minimal Thermal Signature Targets in Infrared Imagery Using Biologically Inspired Vision. Sensors, 21.","DOI":"10.3390\/s21051812"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1007\/s10851-019-00925-9","article-title":"A two-stage method for spectral\u2013spatial classification of hyperspectral images","volume":"62","author":"Chan","year":"2020","journal-title":"J. Math. Imaging Vis."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1117\/12.364049","article-title":"Max-mean and max-median filters for detection of small-targets","volume":"3809","author":"Deshpande","year":"1999","journal-title":"Proc. SPIE"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10539","DOI":"10.1007\/s11042-017-4592-2","article-title":"Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection","volume":"77","author":"Deng","year":"2017","journal-title":"Multimedia Tools Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"105503","DOI":"10.1109\/ACCESS.2019.2932729","article-title":"A Difference-Based Local Contrast Method for Infrared Small Target Detection Under Complex Background","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lu, Y., Dong, L., Zhang, T., and Xu, W. (2020). A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets. Sensors, 20.","DOI":"10.3390\/s20041237"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chen, F., Huang, M., Ma, Z., Li, Y., and Huang, Q. (2020). An Iterative Weighted-Mean Filter for Removal of High-Density Salt-and-Pepper Noise. Symmetry, 12.","DOI":"10.3390\/sym12121990"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1007\/s10762-009-9518-2","article-title":"Small Target Detection Utilizing Robust Methods of the Human Visual System for IRST","volume":"30","author":"Kim","year":"2009","journal-title":"J. Infrared Millimeter Terahertz Waves"},{"key":"ref_17","first-page":"67","article-title":"The Design of Top-hat Morphological Filter and Application to Infrared Target Detection","volume":"48","author":"Ming","year":"2005","journal-title":"Infr. Phys. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.1109\/LGRS.2019.2912989","article-title":"Infrared Small Target Detection by Density Peaks Searching and Maximum-Gray Region Growing","volume":"16","author":"Huang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/j.infrared.2012.08.004","article-title":"Infrared dim target detection based on visual attention","volume":"55","author":"Wang","year":"2012","journal-title":"Infrared Phys. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1109\/TGRS.2013.2242477","article-title":"A Local Contrast Method for Small Infrared Target Detection","volume":"52","author":"Chen","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"107729","DOI":"10.1016\/j.patcog.2020.107729","article-title":"Infrared small target detection via adaptive M-estimator ring top-hat transformation","volume":"112","author":"Deng","year":"2021","journal-title":"Pattern Recognit."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2168","DOI":"10.1109\/LGRS.2014.2323236","article-title":"A Robust Infrared Small Target Detection Algorithm Based on Human Visual System","volume":"11","author":"Han","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1890","DOI":"10.1109\/LGRS.2016.2616416","article-title":"Effective Infrared Small Target Detection Utilizing a Novel Local Contrast Method","volume":"13","author":"Qin","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1109\/LGRS.2018.2790909","article-title":"Infrared Small Target Detection Utilizing the Multiscale Relative Local Contrast Measure","volume":"15","author":"Han","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","unstructured":"Wu, L., Ma, Y., Fan, F., Wu, M., and Huang, J. (2020). A Double-Neighborhood Gradient Method for Infrared Small Target Detection. IEEE Geosci. Remote Sens. Lett., 1\u20135."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1109\/LGRS.2019.2954578","article-title":"A Local Contrast Method for Infrared Small-Target Detection Utilizing a Tri-Layer Window","volume":"17","author":"Han","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.patcog.2016.04.002","article-title":"Multiscale patch-based contrast measure for small infrared target detection","volume":"58","author":"Wei","year":"2016","journal-title":"Pattern Recognit."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/LGRS.2017.2772030","article-title":"High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection","volume":"15","author":"Shi","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1780","DOI":"10.1109\/LGRS.2018.2856762","article-title":"Tiny and Dim Infrared Target Detection Based on Weighted Local Contrast","volume":"15","author":"Liu","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wang, L., Li, R., Shi, H., Sun, J., Zhao, L., Seah, H.S., Quah, C.K., and Tandianus, B. (2019). Multi-Channel Convolutional Neural Network Based 3D Object Detection for Indoor Robot Environmental Perception. Sensors, 19.","DOI":"10.3390\/s19040893"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gao, X., Luo, H., Wang, Q., Zhao, F., Ye, L., and Zhang, Y. (2019). A Human Activity Recognition Algorithm Based on Stacking Denoising Autoencoder and LightGBM. Sensors, 19.","DOI":"10.3390\/s19040947"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"102949","DOI":"10.1016\/j.dsp.2020.102949","article-title":"Detection and tracking of infrared small target by jointly using SSD and pipeline filter","volume":"110","author":"Ding","year":"2020","journal-title":"Digit. Signal Process."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Yang, X., Wang, F., Bai, Z., Xun, F., Zhang, Y., and Zhao, X. (2021). Deep Learning-Based Congestion Detection at Urban Intersections. Sensors, 21.","DOI":"10.3390\/s21062052"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"146081","DOI":"10.1109\/ACCESS.2019.2944661","article-title":"Detection of Infrared Small Targets Using Feature Fusion Convolutional Network","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"L\u00f3pez-Sastre, R.J., Herranz-Perdiguero, C., Guerrero-G\u00f3mez-Olmedo, R., O\u00f1oro-Rubio, D., and Maldonado-Basc\u00f3n, S. (2019). Boosting Multi-Vehicle Tracking with a Joint Object Detection and Viewpoint Estimation Sensor. Sensors, 19.","DOI":"10.3390\/s19194062"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"106780","DOI":"10.1016\/j.compchemeng.2020.106780","article-title":"Real-time leak detection using an infrared camera and Faster R-CNN technique","volume":"135","author":"Shi","year":"2020","journal-title":"Comput. Chem. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Srivastava, A., Rodriguez, J., Saco, P., Kumari, N., and Yetemen, O. (2021). Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets. Remote Sens., 13.","DOI":"10.3390\/rs13091716"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"107727","DOI":"10.1016\/j.sigpro.2020.107727","article-title":"Fast and robust small infrared target detection using absolute directional mean difference algorithm","volume":"177","author":"Moradi","year":"2020","journal-title":"Signal Process."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/13\/4522\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:24:38Z","timestamp":1760163878000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/13\/4522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":38,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["s21134522"],"URL":"https:\/\/doi.org\/10.3390\/s21134522","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}