Bheema Lakshmi Pradeep, R. Anand, Pavan Vadakattu, Syed Azemuddin, A. Ahmed
{"title":"Design and Implementation of a Real-time Parallel FFT for a Direction-Finding System on an FPGA","authors":"Bheema Lakshmi Pradeep, R. Anand, Pavan Vadakattu, Syed Azemuddin, A. Ahmed","doi":"10.1109/HPEC55821.2022.9926310","DOIUrl":null,"url":null,"abstract":"An FFT is an essential algorithm for radar signal processing in a radar system. Due to increase in computational power of FPGAs, it is possible to perform FFT operation onboard in an airborne vehicle. However, the FPGA resources have become a limitation for processing real-time signals using conventional methods. To address this issue, we have proposed a parallel pipelined FFT architecture that can achieve very high throughput with very low latency, making it capable of processing real-time continuous data. This architecture is implemented in a radar system, which works from L band to Ku band. In this radar system, the received RF signal is downconverted into an IF signal of 1 GHz frequency with a 500 MHz bandwidth and converted to digital data using a 10-bit ADC. On the converted digital data, a 512-point FFT is implemented on a Xilinx Virtex-7 XC7VX485T FPGA using 8 parallel channels with 64 data frames and is compared with the conventional IP core-based architecture. The proposed architecture takes 1.307µs to implement FFT, which is 5.15 times faster than the IP core-based architecture and requires fewer arithmetic computations. The overall total number of complex multiplications, complex additions, multipliers & adders were reduced by 10.42%, 30.64%, 10.42% & 23.90% respectively. Apart from very low latency and fewer arithmetic operations, the proposed parallel FFT architecture achieved a throughput of 1.350 Giga Samples per second (Gsps).","PeriodicalId":200071,"journal":{"name":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC55821.2022.9926310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
An FFT is an essential algorithm for radar signal processing in a radar system. Due to increase in computational power of FPGAs, it is possible to perform FFT operation onboard in an airborne vehicle. However, the FPGA resources have become a limitation for processing real-time signals using conventional methods. To address this issue, we have proposed a parallel pipelined FFT architecture that can achieve very high throughput with very low latency, making it capable of processing real-time continuous data. This architecture is implemented in a radar system, which works from L band to Ku band. In this radar system, the received RF signal is downconverted into an IF signal of 1 GHz frequency with a 500 MHz bandwidth and converted to digital data using a 10-bit ADC. On the converted digital data, a 512-point FFT is implemented on a Xilinx Virtex-7 XC7VX485T FPGA using 8 parallel channels with 64 data frames and is compared with the conventional IP core-based architecture. The proposed architecture takes 1.307µs to implement FFT, which is 5.15 times faster than the IP core-based architecture and requires fewer arithmetic computations. The overall total number of complex multiplications, complex additions, multipliers & adders were reduced by 10.42%, 30.64%, 10.42% & 23.90% respectively. Apart from very low latency and fewer arithmetic operations, the proposed parallel FFT architecture achieved a throughput of 1.350 Giga Samples per second (Gsps).