Zoom FFT for precise spectrum calculation in FMCW radar using FPGA

Al-Qudsi, Belal; Joram, Niko; Strobel, Axel; Ellinger, Frank

doi:10.1109/prime.2013.6603180

Cited by 10 publications

(4 citation statements)

References 3 publications

(6 reference statements)

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“…Similarly, signal-processing algorithms used in industrial applications can be applied to improve range accuracy. Liquid-level sensing radar systems use algorithms like Zoom-FFT [67]. There is plenty of room for exploration and use in the very-high-accuracy landing requirements of UASs or commercial aviation.…”

Section: Future Workmentioning

confidence: 99%

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Awan,

Dalveren,

Kara

et al. 2024

Drones

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Precise altitude data are indispensable for flight navigation, particularly during the autonomous landing of unmanned aerial systems (UASs). Conventional light and barometric sensors employed for altitude estimation are limited by poor visibility and temperature conditions, respectively, whilst global positioning system (GPS) receivers provide the altitude from the mean sea level (MSL) marred with a slow update rate. To cater to the landing safety requirements, UASs necessitate precise altitude information above ground level (AGL) impervious to environmental conditions. Radar altimeters, a mainstay in commercial aviation for at least half a century, realize these requirements through minimum operational performance standards (MOPSs). More recently, the proliferation of 5G technology and interference with the universally allocated band for radar altimeters from 4.2 to 4.4 GHz underscores the necessity to explore novel avenues. Notably, there is no dedicated MOPS tailored for radar altimeters of UASs. To gauge the performance of a radar altimeter offering for UASs, existing MOPSs are the de facto choice. Historically, frequency-modulated continuous wave (FMCW) radars have been extensively used in a broad spectrum of ranging applications including radar altimeters. Modern monolithic millimeter wave (mmWave) automotive radars, albeit designed for automotive applications, also employ FMCW for precise ranging with a cost-effective and compact footprint. Given the technology maturation with excellent size, weight, and power (SWaP) metrics, there is a growing trend in industry and academia to explore their efficacy beyond the realm of the automotive industry. To this end, their feasibility for UAS altimetry remains largely untapped. While the literature on theoretical discourse is prevalent, a specific focus on mmWave radar altimetry is lacking. Moreover, clutter estimation with hardware specifications of a pure look-down mmWave radar is unreported. This article argues the applicability of MOPSs for commercial aviation for adaptation to a UAS use case. The theme of the work is a tutorial based on a simplified mathematical and theoretical discussion on the understanding of performance metrics and inherent intricacies. A systems engineering approach for deriving waveform specifications from operational requirements of a UAS is offered. Lastly, proposed future research directions and insights are included.

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Section: Future Workmentioning

confidence: 99%

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Awan,

Dalveren,

Kara

et al. 2024

Drones

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“…It blends complex down-conversion, low-pass filtering, and sample-rate change by way of decimation, thereby improving the frequency resolution [ 26 ]. Al-Qudsi et al [ 27 ] presented an implementation method of the ZFFT approach to estimate the spectral peak in the FMCW radar, utilizing a field programmable gate array (FPGA). This algorithm can decrease the complexity of calculations and alleviate the influence of picket fence effect.…”

Section: Introductionmentioning

confidence: 99%

A Spectrum Correction Algorithm Based on Beat Signal of FMCW Laser Ranging System

Hao

Song

Wang

et al. 2021

Sensors

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The accuracy of target distance obtained by a frequency modulated continuous wave (FMCW) laser ranging system is often affected by factors such as white Gaussian noise (WGN), spectrum leakage, and the picket fence effect. There are some traditional spectrum correction algorithms to solve the problem above, but the results are unsatisfactory. In this article, a decomposition filtering-based dual-window correction (DFBDWC) algorithm is proposed to alleviate the problem caused by these factors. This algorithm reduces the influence of these factors by utilizing a decomposition filtering, dual-window in time domain and two phase values of spectral peak in the frequency domain, respectively. With the comparison of DFBDWC and these traditional algorithms in simulation and experiment on a built platform, the results show a superior performance of DFBDWC based on this platform. The maximum absolute error of target distance calculated by this algorithm is reduced from 0.7937 m of discrete Fourier transform (DFT) algorithm to 0.0407 m, which is the best among all mentioned spectrum correction algorithms. A high performance FMCW laser ranging system can be realized with the proposed algorithm, which has attractive potential in a wide scope of applications.

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“…Thereby a model order estimation should be carried out to determine the relevant number of frequencies with a certain risk that undetected frequencies can be interpreted as noise components [13]. Other approaches such as the Chirp-Z transform (CZT) or the ZoomFFT (ZFFT) are narrow-band analysis techniques [24][25][26], which are computational efficient and estimate therefore the spectrum during the spectral calculation process. The ZFFT realizes the same frequency resolution as the standard FFT, even if it is calculated based on a shorter time signal segment.…”

Section: Introductionmentioning

confidence: 99%

Amplitude and frequency estimator for aperiodic multi-frequency noisy vibration signals of a tram gearbox

Wolf¹,

Rudolph²,

Kanoun³

2021

J. vibroeng.

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Sinusoidal parameter estimation for determining frequency position and amplitude is challenging for noisy short vibration signals, e.g. from machines or human vibrations. In this paper, we propose the "Trimmed Window Discrete Fourier Transform" (TWDFT) estimator, which uses for every frequency a one-point discrete Fourier transform (DFT) to determine the corresponding spectral amplitude. To avoid leakage effects, it cuts the time interval so that it corresponds to an integer number of period durations. To evaluate the estimator performance, we compare it with relevant estimators such as the Cramer-Rao lower bound (CRLB) and the spectral spline interpolation applied on a noisy mono-frequent test signal with a fractional frequency. For the estimated parameters, the mean squared errors (MSE) are calculated and compared as a function of the signal-to-noise ratio (SNR). The advantages of the TWDFT estimator can be seen over the whole SNR range. The TWDFT estimates are better than the fast Fourier transform (FFT) starting at a SNR of -6 dB. At a SNR of 30 dB, the estimator meets the real value of the frequency and reaches similar results as the CRLB. The application of the TWDFT estimator as a short-time analysis on a vibration signal of a tram gearbox shows a significantly more differentiated time-frequency analysis compared to a short-time Fourier transform (STFT).

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Zoom FFT for precise spectrum calculation in FMCW radar using FPGA

Cited by 10 publications

References 3 publications

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

A Spectrum Correction Algorithm Based on Beat Signal of FMCW Laser Ranging System

Amplitude and frequency estimator for aperiodic multi-frequency noisy vibration signals of a tram gearbox

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