Design and Implementation of a Real-time Parallel FFT for a Direction-Finding System on an FPGA

Bheema Lakshmi Pradeep, R. Anand, Pavan Vadakattu, Syed Azemuddin, A. Ahmed
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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).
基于FPGA的测向系统实时并行FFT的设计与实现
FFT是雷达系统中雷达信号处理的重要算法。由于fpga计算能力的提高,在机载飞行器上执行FFT操作成为可能。然而,FPGA资源已经成为使用传统方法处理实时信号的限制。为了解决这个问题,我们提出了一个并行流水线FFT架构,可以实现非常高的吞吐量和非常低的延迟,使其能够处理实时连续数据。该体系结构在L波段到Ku波段的雷达系统中实现。在该雷达系统中,接收到的射频信号被下变频为频率为1ghz、带宽为500mhz的中频信号,并通过10位ADC转换为数字数据。在转换后的数字数据上,在Xilinx Virtex-7 XC7VX485T FPGA上实现了一个512点的FFT,使用8个并行通道和64个数据帧,并与传统的基于IP核的架构进行了比较。该架构实现FFT的时间为1.307µs,比基于IP核的架构快5.15倍,并且需要更少的算术计算。复乘法、复加法、乘法器和加法器的总次数分别减少了10.42%、30.64%、10.42%和23.90%。除了非常低的延迟和更少的算术运算外,所提出的并行FFT架构实现了每秒1.350千兆样本(Gsps)的吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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