Improved Frequency Estimation for Range-Finding Applications using Phase Unwrapping

The Fast Fourier Transform (FFT) is a common signal processing operation used in frequency estimation, a technique that has many applications in a wide range of fields including radar, LiDAR, sonar, medical sciences, telecommunications, and metrology. However, in real-time applications, computational intensity often imposes restrictions on frequency resolution, and consequently introducing spectral errors. To address this limitation, the frequency resolution of FFT can be refined for enhanced accuracy by unwrapping the phase information of the frequency component, while maintaining the required FFT points and sampling rate. This paper presents an analysis of diverse windowing techniques, showcasing the potential enhancement of FFT spectral accuracy, particularly for precision-centric measurements. The proposed method is adaptable for deployment in both programmable and non-programmable real-time systems, including Embedded Systems and Field-Programmable Gate Arrays (FPGAs).