Automotive radars: A review of signal processing techniques

Patole, Sujeet; Torlak, Murat; Wang, Dan; Ali, Muhammad Yasir

doi:10.1109/msp.2016.2628914

Cited by 799 publications

(428 citation statements)

References 54 publications

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“…Radar systems operate by transmitting a signal and listening for reflected, time delayed signals. Various signal‐processing techniques can be used to simultaneously obtain the range, velocity, and angle of arrival of multiple targets . Here, HFSS SBR+ computes range profiles and Doppler‐range maps using frequency‐modulated interrupted continuous wave (FMiCW).…”

Section: Radar Scene Modelingmentioning

confidence: 99%

“…Various signalprocessing techniques can be used to simultaneously obtain the range, velocity, and angle of arrival of multiple targets. 18 Here, HFSS SBR+ computes range profiles and Dopplerrange maps using frequency-modulated interrupted continuous wave (FMiCW). The radar signal is a 300 MHz up chirp signal centered at 77 GHz with a pulse repetition frequency of 41.07 KHz.…”

Section: Radar Scene Modelingmentioning

confidence: 99%

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Full physics simulation of terrain‐adaptive 77 GHz automotive radar for early pedestrian detection

Chipengo

2019

Micro & Optical Tech Letters

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Fully autonomous vehicles and the need to improve road safety have led to increased demands on the reliability of various advanced driver assistance systems (ADAS). Automotive radar is a key component of ADAS as it adds both safety and comfort features in vehicles. A key challenge in developing automotive radar is demonstrating reliability especially in corner cases. Building and testing radar systems for corner cases is time‐consuming, costly, and impractical. Simulation is the only practical way of investigating the countless possible automotive radar corner cases. An interesting corner case is the reduction of radar returns due to sharp road bends. Specifically, crucial targets with low radar cross sections (RCS) such as pedestrians can become invisible to radar when driving around sharp road bends. In this article, a high fidelity, full physics‐based simulation of a 77 GHz automotive radar scene will be used to investigate this corner case. The dependence of radar returns on the position of an ego vehicle negotiating a sharp bend will be presented. Results from these simulations show a pedestrian disappearing from view at an approaching angle of 60∘ with a degradation of over 40 dB in pedestrian radar returns. Using results from this study, a terrain‐adaptive technique for improving radar target detection capabilities is proposed. This technique is shown to improve pedestrian radar returns by over 26 dB. Improved radar returns can help in early detection of pedestrians and other relevant targets. Early target detection can help reduce accidents while potentially saving pedestrian lives.

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Section: Radar Scene Modelingmentioning

confidence: 99%

Section: Radar Scene Modelingmentioning

confidence: 99%

Full physics simulation of terrain‐adaptive 77 GHz automotive radar for early pedestrian detection

Chipengo

2019

Micro & Optical Tech Letters

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“…Among the main goals of intelligent transportation systems (ITS) are (i) safety: reduce safety threats encountered due to human impact, and (ii) efficiency: provide transportation opportunities in a way that is ecologically and economically sustainable. Two important technological components are automotive radar and vehicular communication, especially for advanced driver assistant systems and self-driving cars [1], [2], serving complementary purposes.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we propose a joint radar and communication (RadCom) system operating in the 77 GHz radar band, termed RadChat, which controls and coordinates automotive radar sensors among vehicles via wireless communications in order to mitigate interference. RadChat is an integrated system with both radar and communication functionality, built with minimal modification from standard frequency modulated continuous-wave (FMCW) based automotive radar, which is the most common, cheap and robust radar format used in the automotive sector today [1]. Our main contributions are as follows:…”

Section: Introductionmentioning

confidence: 99%

RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation

Aydoğdu

Keskin

Garcia

et al. 2021

IEEE Trans. Intell. Transport. Syst.

107

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In the automotive sector, both radars and wireless communication are susceptible to interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate interference in both systems. This article analyses the mutual interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of interference among FMCW based automotive radars, including self-interference, using radar communications. The results show that RadChat can significantly reduce radar mutual interference in single-hop vehicular networks in less than 80 ms.

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“…The most commonly used LFM (Linear frequency modulation) waveform radar provides high range and velocity resolution, but it can not solve the problem of ghost targets in multiple targets situation. In addition, the radar system of FSK (Frequency shift keying) waveform has high velocity resolution and can avoid the ghost targets, but it is unable to measure the stationary target and multiple targets with the same radial velocity [1,2,3].…”

Section: Introductionmentioning

confidence: 99%

The design and implementation of automotive radar system based on MFSK waveform

2018

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Abstract. As a driving aid system, automotive radar plays a more and more important role in reducing traffic accidents. In this paper, a simple and efficient automotive radar system based on MFSK (Multiple frequency shift keying) is designed, the system structure and implementation algorithm is presented. This system uses FPGA as the signal processing unit to ensure the response speed. In addition, the designed MFSK waveform algorithm achieved high precision and unambiguous measurement. The effectiveness of the system is verified by experiments and field measurements.

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Automotive radars: A review of signal processing techniques

Cited by 799 publications

References 54 publications

Full physics simulation of terrain‐adaptive 77 GHz automotive radar for early pedestrian detection

Full physics simulation of terrain‐adaptive 77 GHz automotive radar for early pedestrian detection

RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation

The design and implementation of automotive radar system based on MFSK waveform

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