{"title":"在LabVIEW和USRP上实现的FMCW雷达信号处理中拍频提取算法和互相关算法的性能比较","authors":"Jesrey Martin S. Macasero, Olga Joy L. Gerasta","doi":"10.1109/HNICEM48295.2019.9073501","DOIUrl":null,"url":null,"abstract":"There are two prominent ways of implementing signal processing of FMCW radar in SDRs, namely i) the Beat Frequency Extraction Algorithm and ii) Cross Correlation Algorithm. The former is done by numerical mixing of the reference signal and the received signal first and then performing an FFT to detect the beat frequency that is then processed to output range information. Moreover, the latter is done by using cross correlation on the reference signal and the received signal. The aim of this paper is to scrutinize these two algorithms when they are implemented on the NI-USRP SDR platform and determine which is best for FMCW radar target detection accuracy. This paper gives guidance on the pros and cons of choosing such algorithm when being implemented on the USRP platform with LabVIEW as the development environment. The implementation of the two systems are based on these conditions: i) Carrier signal is 2Ghz, ii) Loopback cable is RG58 with lengths= 6m, 8m, 14m, 22m, and iii) Output RF Power of device is 70mW. Given the performance criteria of this paper, the Beat Frequency algorithm performed best compared to the Cross-Correlation algorithm.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"61 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Performance Comparison of Beat Frequency Extraction Algorithm and Cross Correlation Algorithm for FMCW Radar Signal Processing Implemented on LabVIEW and USRP\",\"authors\":\"Jesrey Martin S. Macasero, Olga Joy L. Gerasta\",\"doi\":\"10.1109/HNICEM48295.2019.9073501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are two prominent ways of implementing signal processing of FMCW radar in SDRs, namely i) the Beat Frequency Extraction Algorithm and ii) Cross Correlation Algorithm. The former is done by numerical mixing of the reference signal and the received signal first and then performing an FFT to detect the beat frequency that is then processed to output range information. Moreover, the latter is done by using cross correlation on the reference signal and the received signal. The aim of this paper is to scrutinize these two algorithms when they are implemented on the NI-USRP SDR platform and determine which is best for FMCW radar target detection accuracy. This paper gives guidance on the pros and cons of choosing such algorithm when being implemented on the USRP platform with LabVIEW as the development environment. The implementation of the two systems are based on these conditions: i) Carrier signal is 2Ghz, ii) Loopback cable is RG58 with lengths= 6m, 8m, 14m, 22m, and iii) Output RF Power of device is 70mW. Given the performance criteria of this paper, the Beat Frequency algorithm performed best compared to the Cross-Correlation algorithm.\",\"PeriodicalId\":6733,\"journal\":{\"name\":\"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )\",\"volume\":\"61 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HNICEM48295.2019.9073501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM48295.2019.9073501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Comparison of Beat Frequency Extraction Algorithm and Cross Correlation Algorithm for FMCW Radar Signal Processing Implemented on LabVIEW and USRP
There are two prominent ways of implementing signal processing of FMCW radar in SDRs, namely i) the Beat Frequency Extraction Algorithm and ii) Cross Correlation Algorithm. The former is done by numerical mixing of the reference signal and the received signal first and then performing an FFT to detect the beat frequency that is then processed to output range information. Moreover, the latter is done by using cross correlation on the reference signal and the received signal. The aim of this paper is to scrutinize these two algorithms when they are implemented on the NI-USRP SDR platform and determine which is best for FMCW radar target detection accuracy. This paper gives guidance on the pros and cons of choosing such algorithm when being implemented on the USRP platform with LabVIEW as the development environment. The implementation of the two systems are based on these conditions: i) Carrier signal is 2Ghz, ii) Loopback cable is RG58 with lengths= 6m, 8m, 14m, 22m, and iii) Output RF Power of device is 70mW. Given the performance criteria of this paper, the Beat Frequency algorithm performed best compared to the Cross-Correlation algorithm.