{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T12:22:42Z","timestamp":1784290962128,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:00:00Z","timestamp":1764806400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Intruder Detection and Avoidance System","award":["POIR.01.02.00-00-0018\/15-IDAAS"],"award-info":[{"award-number":["POIR.01.02.00-00-0018\/15-IDAAS"]}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"crossref","award":["2014\u20132020"],"award-info":[{"award-number":["2014\u20132020"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Small and medium Unmanned Aerial Vehicles (UAVs) are commonly equipped with diverse sensors for situational awareness, including cameras, Frequency-Modulated Continuous-Wave (FMCW) radars, Light Detection and Ranging (LiDAR) systems, and ultrasonic sensors. However, optical systems are constrained by adverse weather and darkness, while the limited detection range of compact FMCW radars-typically a few hundred meters-is often insufficient for higher-speed UAVs, particularly those operating Beyond Visual Line of Sight (BVLOS). This paper presents a Collision Avoidance System (CAS) based on a lightweight pulse radar, targeting medium UAV platforms (10\u2013300 kg MTOM) where installing large, nose-mounted radars is impractical. The system is designed for obstacle detection at ranges of 1\u20133 km, directly addressing the standoff distance limitations of conventional sensors. Beyond its primary sensing function, the pulse architecture offers several operational advantages. Its lower time-averaged power also results in a reduced electromagnetic footprint, mitigating interference and supporting emission-control objectives. Furthermore, pulse radar offers greater robustness against interference in dense electromagnetic environments and lower power consumption, both of which directly enhance UAV operational endurance. Field tests demonstrated a one-to-one correspondence between visually identified objects and radar detections across 1\u20133 km, with PFA = 1.5%, confirming adequate standoff for tens of seconds of maneuvering time, with range resolution of 3.75 m and average system power below 80 W.<\/jats:p>","DOI":"10.3390\/s25237392","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T18:42:02Z","timestamp":1764960122000},"page":"7392","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Lightweight and Compact Pulse Radar for UAV Platforms for Mid-Air Collision Avoidance"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7914-5709","authenticated-orcid":false,"given":"Dawid","family":"Sysak","sequence":"first","affiliation":[{"name":"Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5689-8292","authenticated-orcid":false,"given":"Arkadiusz","family":"Byndas","sequence":"additional","affiliation":[{"name":"Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0814-1444","authenticated-orcid":false,"given":"Tomasz","family":"Karas","sequence":"additional","affiliation":[{"name":"Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grzegorz","family":"Jaromi","sequence":"additional","affiliation":[{"name":"EUROTECH Ltd., 39-300 Mielec, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Munir, A., Siddiqui, A.J., Anwar, S., El-Maleh, A., Khan, A.H., and Rehman, A. (2024). Impact of Adverse Weather and Image Distortions on Vision-Based UAV Detection: A Performance Evaluation of Deep Learning Models. Drones, 8.","DOI":"10.3390\/drones8110638"},{"key":"ref_2","unstructured":"FAA (2025). Aerospace Forecast Fiscal Years 2025\u20132045: Emerging Aviation Entrants: Unmanned Aircraft System and Advanced Air Mobility, Federal Aviation Administration (FAA). Report."},{"key":"ref_3","unstructured":"EUROCONTROL (2022). U-Space Services Implementation Monitoring Report, European Organisation for the Safety of Air Navigation (EUROCONTROL). Report."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Jaiswal, K., and Vashisth, A. (2023, January 12\u201313). A Comprehensive Analysis of UAV Collision Avoidance Techniques for Enhanced Aerial Safety. Proceedings of the 2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM), Dubai, United Arab Emirates.","DOI":"10.1109\/ICCAKM58659.2023.10449529"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105139","DOI":"10.1109\/ACCESS.2020.3000064","article-title":"Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches","volume":"8","author":"Yasin","year":"2020","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Lai, Y.C., and Lin, T.Y. (2024). Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment. Remote Sens., 16.","DOI":"10.3390\/rs16050756"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhao, D., and Cao, Y. (2022). Image Quality Enhancement with Applications to Unmanned Aerial Vehicle Obstacle Detection. Aerospace, 9.","DOI":"10.3390\/aerospace9120829"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Xiong, W., Wang, Z., Niu, M., and Liang, Q. (2024, January 27\u201329). Low-altitude UAV Autonomous Obstacle Avoidance using LiDAR Sensor Fusion. Proceedings of the 2024 10th International Conference on Mechanical and Electronics Engineering (ICMEE), Xi\u2019an, China.","DOI":"10.1109\/ICMEE63700.2024.11025217"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Pedro, B.M.B., and Marta, A.C. (2025). On the Development of a Sense and Avoid System for Small Fixed-Wing UAV. Sensors, 25.","DOI":"10.3390\/s25082460"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Park, J., and Cho, N. (2020). Collision Avoidance of Hexacopter UAV Based on LiDAR Data in Dynamic Environment. Remote Sens., 12.","DOI":"10.3390\/rs12060975"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.isprsjprs.2022.12.021","article-title":"Perception and sensing for autonomous vehicles under adverse weather conditions: A survey","volume":"196","author":"Zhang","year":"2023","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","unstructured":"Benewake (2025, September 18). TFA1200-L Kilometer-Level Lightweight Single-Point LiDAR. Available online: https:\/\/en.benewake.com\/tfa1200-kilometer-level-lidar."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wessendorp, N., Dinaux, R., Dupeyroux, J., and de Croon, G.C.H.E. (October, January 27). Obstacle Avoidance onboard MAVs using a FMCW Radar. Proceedings of the 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic.","DOI":"10.1109\/IROS51168.2021.9635901"},{"key":"ref_14","unstructured":"Skolnik, M.I. (2001). Introduction to Radar Systems, McGraw-Hill. [3rd ed.]."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Xu, Y., Zhu, M., Xu, Y., and Liu, M. (2019, January 28\u201330). Design and Implementation of UAV Obstacle Avoidance System. Proceedings of the 2019 2nd International Conference on Safety Produce Informatization (IICSPI), Chongqing, China.","DOI":"10.1109\/IICSPI48186.2019.9095902"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"De Simone, M.C., Rivera, Z.B., and Guida, D. (2018). Obstacle Avoidance System for Unmanned Ground Vehicles by Using Ultrasonic Sensors. Machines, 6.","DOI":"10.3390\/machines6020018"},{"key":"ref_17","unstructured":"Kemkemian, S., Nouvel-Fiani, M., Cornic, P., Bihan, P.L., and Garrec, P. (2009, January 12\u201316). Radar systems for \u201cSense and Avoid\u201d on UAV. Proceedings of the 2009 International Radar Conference \u201cSurveillance for a Safer World\u201d (RADAR 2009), Bordeaux, France."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1017\/S0263574713000659","article-title":"UAV-borne X-band radar for collision avoidance","volume":"32","author":"Moses","year":"2014","journal-title":"Robotica"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kwag, Y.K., Choi, M.S., Jung, C.H., and Hwang, K.Y. (2006, January 16\u201319). Collision Avoidance Radar for UAV. Proceedings of the 2006 CIE International Conference on Radar, Shanghai, China.","DOI":"10.1109\/ICR.2006.343231"},{"key":"ref_20","unstructured":"(2019). Unmanned Aircraft Systems Airworthiness Requirements (USAR) (Standard No. NATO STANDARD AEP-4671)."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Andres, S., Lanzuela, J., Ocabo, A., Villafranca, A., Alonso, R., Salinas, I., and Heras, C. (2024, January 21\u201325). FMCW Radar system for UAV tracking and identification by MDS recognition. Proceedings of the 2024 International Radar Conference (RADAR), Rennes, France.","DOI":"10.1109\/RADAR58436.2024.10994094"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"De Quevedo, \u00c1.D., Urzaiz, F.I., Menoyo, J.G., and L\u00f3pez, A.A. (2018, January 27\u201331). Drone Detection and RCS Measurements with Ubiquitous Radar. Proceedings of the 2018 International Conference on Radar (RADAR), Oklahoma City, OK, USA.","DOI":"10.1109\/RADAR.2018.8557320"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1030","DOI":"10.1109\/JSTSP.2021.3066887","article-title":"Long Range, Low SWaP-C FMCW Radar","volume":"15","author":"Lies","year":"2021","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_24","unstructured":"(2025, October 29). Echodyne Corp. EchoFlight 5SE: Data Sheet, Available online: https:\/\/www.echodyne.com\/media\/s4ufvdd5\/ts-echoflight-echodyne_5se.pdf."},{"key":"ref_25","unstructured":"Lime Microsystems (2025, September 15). LMS7002M: Field Programmable RF Transceiver IC. Available online: https:\/\/limemicro.com\/silicon\/lms7002m."},{"key":"ref_26","unstructured":"AMD Xilinx (2025, September 16). 7 Series FPGAs Data Sheet: Overview, DS180 (v2.6.1). Available online: https:\/\/docs.amd.com\/v\/u\/en-US\/ds180_7Series_Overview."},{"key":"ref_27","unstructured":"Byndas, A., Hofman, M., and Kabacik, P. (2025, January 4\u20138). Gain and Dual-polarization Performance Enhancement in Medium-gain Antenna Arrays Featuring Thin Thickness. Proceedings of the 2025 Photonics & Electromagnetics Research Symposium (PIERS) Abstracts, Abu Dhabi, United Arab Emirates. Available online: https:\/\/abdb2025.piers.org\/preview.html?pid=241116183547."},{"key":"ref_28","unstructured":"Song, Y., Meng, X., and Qu, F. (2009, January 20\u201322). A new CFAR method based on test cell statistics. Proceedings of the 2009 IET International Radar Conference, Guilin, China."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1109\/TAES.1983.309350","article-title":"Radar CFAR Thresholding in Clutter and Multiple Target Situations","volume":"AES-19","author":"Rohling","year":"1983","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_30","unstructured":"Yang, J.M., and Kim, W.W. (2008, January 10\u201312). Performance analysis of a minimum selected cell-averaging CFAR detection. Proceedings of the 2008 11th IEEE International Conference on Communication Technology, Hangzhou, China."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, J., Dong, Y., Liu, N., Huang, Y., Jiang, X., and Sun, J. (2025). A Novel Copula-Based Multi-Feature CFAR Framework for Radar Target Detection. Remote Sens., 17.","DOI":"10.3390\/rs17132299"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Sysak, D., Jaromi, G., and Biernacki, P. (2021, January 23\u201325). Implementation and verification of Nonlinear chirp signals in hardware system. Proceedings of the 2021 IEEE Region 10 Symposium (TENSYMP), Jeju, Republic of Korea.","DOI":"10.1109\/TENSYMP52854.2021.9550831"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1049\/rsn2.12028","article-title":"Efficient radar detection of weak manoeuvring targets using a coarse-to-fine strategy","volume":"15","author":"Liu","year":"2021","journal-title":"IET Radar, Sonar Navig."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Jaromi, G., Kabacik, P., Sysak, D., and Makowski, R. (2021, January 24\u201326). Structure and Software Elements of Enavi Radar for Large Drones. Proceedings of the 2021 28th International Conference on Mixed Design of Integrated Circuits and System, Lodz, Poland.","DOI":"10.23919\/MIXDES52406.2021.9497600"},{"key":"ref_35","unstructured":"Karas, T., Magiera, W., Kabacik, P., and Jaromi, G. (2025, January 4\u20138). Time and Spectral Characteristics of X-band Radar Echoes Reflected from Wind Turbine with Rotating Rotor. Proceedings of the 2025 Photonics & Electromagnetics Research Symposium (PIERS) Abstracts, Abu Dhabi, United Arab Emirates. Available online: https:\/\/abdb2025.piers.org\/preview.html?pid=241118005147."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Asif, A., Kandeepan, S., and Evans, R.J. (2023). Passive Radar Tracking in Clutter Using Range and Range-Rate Measurements. Sensors, 23.","DOI":"10.3390\/s23125451"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Son, S., Lee, I., Cha, J., and Choi, H. (2023). Online Learning-Based Hybrid Tracking Method for Unmanned Aerial Vehicles. Sensors, 23.","DOI":"10.3390\/s23063270"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1049\/rsn2.12624","article-title":"Investigations into optimum non-periodic bursts scheme in radar pulse train designed for fixed-wing drone detections by multi-function radar","volume":"18","author":"Gmyrek","year":"2024","journal-title":"IET Radar Sonar Navig."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3121","DOI":"10.1109\/TITS.2016.2539002","article-title":"Cognitive Chaotic UWB-MIMO Detect-Avoid Radar for Autonomous UAV Navigation","volume":"17","author":"Nijsure","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Wei, R., and Huang, S. (2024). Cognitive Control Architecture for the Practical Realization of UAV Collision Avoidance. Sensors, 24.","DOI":"10.3390\/s24092790"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/23\/7392\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T05:30:01Z","timestamp":1764999001000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/23\/7392"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,4]]},"references-count":40,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["s25237392"],"URL":"https:\/\/doi.org\/10.3390\/s25237392","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,4]]}}}