Interference Compression and Mitigation for Automotive FMCW Radar Systems

Rameez, Muhammad; Pettersson, Mats I.; Dahl, Mattias

doi:10.1109/jsen.2022.3204505

Cited by 10 publications

(3 citation statements)

References 31 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The fan beam pattern is advantageous in point-to-multipoint connectivity in various indoor mmWave wireless industrial applications which include sensing and monitoring industrial processes for data collection and proactive analysis, predictive maintenance, asset tracking, and collision avoidance [19]- [22]. Moreover, the proposed wideband 60 GHz array is advantageous to cover a wide sectoral region for efficient energy transport over 60 GHz for IWSN [23].…”

Section: Introductionmentioning

confidence: 99%

AWideband Frequency Beam-Scanning Antenna Array for Millimeter-Wave Industrial Wireless Sensing Applications

Jabbar,

Kazim,

Pang

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

The 57-71 GHz millimeter-wave (mmWave) Industrial, Scientific, and Medical (ISM) band holds significant potential for enhancing the performance of next-generation industrial wireless applications. This paper first presents the design and analysis of a compact and high-performance 8-element series-fed frequency beam-scanning array designed to cover the entire 21.87% fractional bandwidth of the 57-71 GHz ISM band. Using this as a subarray, a hybrid parallel-series feed topology is designed to construct a 64element (8 × 8) planar array with high-gain directional beams. The planar array provides a peak measured gain of 20.12 dBi at 64 GHz and maintains a flat gain of over 19.23 dBi throughout the band, with a 1 dB gain bandwidth of 13 GHz. Its narrow directional beams provide an average half-power beamwidth of 9.7° and 11.78° in the elevation and azimuth planes, facilitating point-to-point mmWave connectivity and high-resolution beam scanning. The inherent phase variation of the series-fed topology is employed to produce a beamscanning range of 40° within the 57-71 GHz band, with a scan loss of less than 1 dB. The proposed array is a low-cost, and reproducible solution for seamless integration with V-band mmWave equipment, as elucidated through practical demonstration frameworks using mmWave power sensor and EK1HMC6350 evaluation board. The proposed array is well-suited for emerging industrial wireless sensing and imaging applications, and mmWave frequency scanning radars. Its versatility extends to various 60 GHz protocols such as IEEE 802.11ay, IEEE 802.11ad, IEEE 802.15.3c/d, WirelessHD, and other customized industrial protocols such as WirelessHP.

show abstract

Section: Introductionmentioning

confidence: 99%

AWideband Frequency Beam-Scanning Antenna Array for Millimeter-Wave Industrial Wireless Sensing Applications

Jabbar,

Kazim,

Pang

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

show abstract

“…Ref. [ 28 ] advocates for interference mitigation in the correlation domain, using matched filtering combined with autoregressive models. Ref.…”

Section: Introductionmentioning

confidence: 99%

An Interference Mitigation Method for FMCW Radar Based on Time–Frequency Distribution and Dual-Domain Fusion Filtering

Zhou,

Cao,

Zhang

et al. 2024

Sensors

View full text Add to dashboard Cite

Radio frequency interference (RFI) significantly hampers the target detection performance of frequency-modulated continuous-wave radar. To address the problem and maintain the target echo signal, this paper proposes a priori assumption on the interference component nature in the radar received signal, as well as a method for interference estimation and mitigation via time–frequency analysis. The solution employs Fourier synchrosqueezed transform to implement the radar’s beat signal transformation from time domain to time–frequency domain, thus converting the interference mitigation to the task of time–frequency distribution image restoration. The solution proposes the use of image processing based on the dual-tree complex wavelet transform and combines it with the spatial domain-based approach, thereby establishing a dual-domain fusion interference filter for time–frequency distribution images. This paper also presents a convolutional neural network model of structurally improved UNet++, which serves as the interference estimator. The proposed solution demonstrated its capability against various forms of RFI through the simulation experiment and showed a superior interference mitigation performance over other CNN model-based approaches.

show abstract

“…In recent years, advanced driving assistance systems (ADAS) for automobiles have been increasingly widely used, and millimeter wave automotive radar plays an important role [l,2]. When cars are densely packed on the road, the problem of mutual interference between radars brings a new challenge to traffic safety [3,4,5].If a automotive radar is interfered by another one works in the same frequency band, the performance of the victim radar will decrease badly, and the research on mutual interference alleviation has been a hot topic in the field of automotive electronics technology in the past decade [6,7,8,9]. Most existing methods for mitigating mutual interference can be classified into three methodologies.…”

Section: Introductionmentioning

confidence: 99%

Fast Algorithm for Automotive Radar Target Detection in Mutual Interference

Mingshun,

Weijie,

et al. 2024

IEICE Commun. Express

View full text Add to dashboard Cite

As one of the important sensors for driving assistance, millimeter wave radar is of great significance for automotive safety driving. However, the problem of mutual interference between automotive radar signals is becoming a non negligible threat. Mutual interference can cause a significant performance decrease of radar target detection, and this article proposes a simple and efficient target detection method to address this issue. The proposed method utilizes the distribution difference between target echoes and interference signals in the time-frequency domain to obtain a accumulation vector of spectral peaks, which follow a Poisson distribution. Based on that, the Poisson constant false alarm detection method is proposed to detect target echos effectively at low signal-to-interference ratios. The experimental results show that the detection accuracy of the method is above 95% when the signal-tointerference ratio is below -20dB. In addition, this algorithm does not require interference compression before detecting the target, and its computational complexity is only slightly greater than that of the short time Fourier transform, so it is a fast anti interference detection method.

show abstract

Interference Compression and Mitigation for Automotive FMCW Radar Systems

Cited by 10 publications

References 31 publications

AWideband Frequency Beam-Scanning Antenna Array for Millimeter-Wave Industrial Wireless Sensing Applications

AWideband Frequency Beam-Scanning Antenna Array for Millimeter-Wave Industrial Wireless Sensing Applications

An Interference Mitigation Method for FMCW Radar Based on Time–Frequency Distribution and Dual-Domain Fusion Filtering

Fast Algorithm for Automotive Radar Target Detection in Mutual Interference

Contact Info

Product

Resources

About