Publication Date

2024

Document Type

Dissertation

Committee Members

Chein-In Henry Chen, Ph.D. (Advisor); Saiyu Ren, Ph.D. (Committee Member); Marian Kazimierczuk, Ph.D. (Committee Member); Raymond E. Siferd, Ph.D. (Committee Member); Yan Zhuang, Ph.D. (Committee Member)

Degree Name

Doctor of Philosophy (PhD)

Abstract

In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key optimizations include converting floating-point data to 10-bit integers and replacing complex multipliers in the FFT module with simplified operations. The design begins with an FFT implementation using a 12-bit analog-to-digital converter (ADC) operating at a 2 GHz sampling rate, capturing 512 data points. Improvements such as a multiple-input selection block enhance weak signal amplification while preserving dynamic range, and an upgraded square-root approximation using Chebyshev coefficients reduces FFT output errors. These advancements improve weak signal detection accuracy even in the presence of strong signals, minimizing hardware requirements. The implementation utilized the Xilinx UltraScale+ RFSoC 1275 board, which integrates both RF and digital processing components onto a single chip, offering a compact and efficient solution for wideband receiver designs. The FFT module processes sampled data every 256 ns, evaluating frequencies from 64 MHz to 940 MHz. Experimental results demonstrate the lowest detectable signal strength of 500 uVpp with an approximate dynamic range of 60 dB for a single signal. For two-tone signals, the achievable instantaneous dynamic range is about 40 dB, with the lowest detectable signal strength in the presence of the strongest full-scale signal measured at 10 mVpp. Nyquist Folding (NF) is another key focus, utilizing frequency modulation of the sampling clock to expand bandwidth, with the extent of expansion depending on the Nyquist zone. This technique enables the recovery of the original wideband signal by analyzing the widened bandwidth. A novel two-channel NF scheme is proposed, employing two sampling clocks with slightly different rates to extract Nyquist zone information. This extends the single-channel NF approach, replacing the frequency-modulated clock with two constant but slightly offset sampling rates. Signal detection and characterization are achieved using an FFT frame-based algorithm. The proposed receiver design supports three-signal detection, employing a dual-channel FFT framework. Both channels utilize a 12-bit ADC with a 2 GHz sampling rate and 512 sampled data points. The primary channel processes data at 2 GHz, while the auxiliary channel processes data offset by four times the primary channel’s frequency resolution, resulting in a sampling rate of 1.984 GHz. This frame-based dual-channel FFT design enables the simultaneous detection of three signals, achieving a minimum frequency bin separation of 11.72 MHz. It demonstrates robust performance with a baseline signal strength requirement of 30 mVpp when the signal is positioned adjacent to either side of two other signals and 110 mVpp when situated between two strong signals. This design ensures reliable operation across a range of signal strengths and placements. The individual spectra obtained from both single-channel and dual-channel configurations demonstrate accurate frequency detection. Comparative analysis with MATLAB® software simulations validates the reliability and precision of the proposed design, establishing it as a robust and effective solution for advanced signal detection in modern radar systems.

Page Count

191

Department or Program

Ph.D. in Engineering

Year Degree Awarded

2024

ORCID ID

0009-0003-7024-3868

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