Abstract
AbstractThe low-cost Continuous Wave (CW) radar architecture for object speed detection is presented in this research. An FPGA (Field-Programmable Gate Array) processor is utilized to implement the CW radar dependably and optimally. The suggested approach uses a bank of filters made expressly to extract velocity information from radar signals to compute the target velocity. Depending on the needs of the particular application, the acquired data has either undergone additional processing or been presented in an approachable manner. The implemented design is checked in real-time with a chip scope, functionally simulated, and then inspected with lab instruments to compare all simulated and implemented outcomes. Numerous applications, such as industrial automation, surveillance, and automotive systems, where accurate velocity detection is crucial and low-cost design is required, could benefit from this concept.
Funder
Egyptian Academy for Engineering & Advanced Technology
Publisher
Springer Science and Business Media LLC
Reference20 articles.
1. Cardillo E, Li C, Caddemi A (2021) Embedded heating, ventilation, and air-conditioning control systems: From traditional technologies toward radar advanced sensing. Adv Measure Instrument Leveraging Embedded Syst Rev Sci Instrum 92:061501
2. Shao Y, Chen P, Cao T A grid projection method based on ultrasonic sensor for parking space detection. In: Proceedings of the IGARSS 2018, IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain; pp. 3378–3381, 2018.
3. Son Y, Heo SW (2018) A novel multi-target detection algorithm for automotive FMCW radar. In: Proceedings of the 2018 international conference on electronics, information, and communication (ICEIC), Honolulu, USA; pp 1–3.
4. Han J, Liao Y, Zhang J, Wang S, Li S (2018) Target fusion detection of LiDAR and camera based on the improved YOLO algorithm. Mathematics, vol. 6
5. Salem SG Design and implementation of proposed pipelined adaptive recovery CAMP algorithm for LFMCW radar, Journal of Signal, Image and Video Processing (SIVP), Springer-Verlag London Ltd, 2020.