Mutual interference of pseudorandom noise radar in automotive collision avoidance application at 24 GHz

Liu, Tsung-Hsin; Hsu, Miao-Lin; Tsai, Zou-Min

doi:10.1109/gcce.2016.7800400

Cited by 10 publications

(6 citation statements)

References 6 publications

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“…As shown in Fig. 2, there are three types of received signals: [Phase 2: Estimating K pairs of Doppler and delay] iii) Obtain { fD,k } K k=1 based on ( 10), (12), and (22). iv) Obtain { Td,k } K k =1 based on ( 13), (14), and ( 21).…”

Section: Gsd-ic: Application Of Gsd-st In Fmcw Radar Systemsmentioning

confidence: 99%

“…In [11]- [16], the authors devised new waveforms or modified existing waveforms to avoid the interference. For example, the pseudo-noise coded FMCW radar signals [11], [12] and the orthogonal noise waveform [13] were proposed. In addition, the frequency hopping was used with the FMCW radar system [14] or a method of irregularly changing the sweep time and the bandwidth of the FMCW radar signal was also presented in [15], [16].…”

Section: Introductionmentioning

confidence: 99%

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Geometric Sequence Decomposition-Based Interference Cancellation in Automotive Radar Systems

Lee

2022

IEEE Access

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Radar signals generated from other vehicles can act as interference to ego-vehicle, which degrades the inherent detection performance of radar. In this paper, we address an efficient solution to the interference problem in frequency-modulated continuous wave (FMCW)-based automotive radar systems, named geometric sequence decomposition based interference cancellation (GSD-IC). With the method of GSD-IC, we can decompose the received signal into different non-orthogonal superposed signals, which means the interference signal and the signal reflected from the desired target are separated. It is based on the facts that 1) each single sampled signal can be interpreted as a geometric sequence and 2) the useful physical features, such as the time delay and the Doppler frequency, are extracted after converting the superposition of these geometric sequences into several transformed matrices. Through this approach, we can achieve effective interference signal cancellation while minimizing the loss of meaningful target information. Moreover, the proposed method does not require the generation of specific radar waveforms, and can mitigate interference through signal processing even with existing waveforms. Numerical results show that our algorithm outperforms existing methods in various scenarios.INDEX TERMS Automotive frequency-modulated continuous wave (FMCW) radar, geometric sequence decomposition (GSD), interference cancellation, joint delay and Doppler estimation.

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Section: Gsd-ic: Application Of Gsd-st In Fmcw Radar Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Geometric Sequence Decomposition-Based Interference Cancellation in Automotive Radar Systems

Lee

2022

IEEE Access

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“…Signal processing techniques like the maximally stable extremal regions algorithm are adopted in [26] to effectively estimate and cancel the mutual interference. Interference mitigation using pseudo-random sequences is studied in [15,17,27], which shows considerable elimination of mutual interference in automotive scenarios. Practical system algorithms that efficiently implement random frequency stepping in automotive applications have been filed by our team in these two patents [28,29] suggesting a reduced interference when utilizing this scheme.…”

Section: Brief Review Of Existing Work On Automotive Radar Interfementioning

confidence: 99%

Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences

Skaria

Al‐Hourani

Evans

et al. 2019

Sensors

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The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.

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“…As interference increases with multiple users, the reliability of assisted driving systems can degrade [9]. These issues motivate the use of specialized, less-predictable waveforms [10][11][12][13][14][15]. Thus, we propose the use of solvable chaos as it exhibits noise-like properties and may be optimally detected using a simple matched filter [16].…”

Section: Introductionmentioning

confidence: 99%

“…This issue is common in many realistic scenarios involving vehicles [6][7][8][9], mobile robots [23,24], and drones [25][26][27]. One successful mitigation technique requires user-specific [15], entropic (noisy) waveforms for spread spectrum techniques such as those used in sonar [10,11] and radar [12][13][14]28] systems. Throughout this section, we provide a brief description of the limitations of FMCW ranging in order to motivate the use of user-specific, noisy waveforms generated from a solvable chaotic source.…”

Section: Introductionmentioning

confidence: 99%

Generating and Detecting Solvable Chaos at Radio Frequencies with Consideration to Multi-User Ranging

Beal

Cohen

Syed

2020

Sensors

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High entropy waveforms exhibit desirable correlation properties in radar and sonar applications when multiple systems are used in close proximity. Unfortunately, the information content of these signals can impose high sampling requirements for digital detection techniques. Solvable chaotic oscillators have been proposed to address such issues due to their simple, matched filters, where hardware has been demonstrated with a bandwidth of 10–20 kHz. To extend applications of these systems, we present theory, design, and experimental verification of solvable chaos at 1 MHz using simple off-the-shelf components. The waveforms produced by this system were propagated over a 2.45 GHz RF link and detected with an RLC-based, purely analog matched filter. Further, we show that properties of this special class of chaotic systems can be exploited to yield RF noise sources that are generally advantageous for multi-user ranging applications when compared to conventional techniques. The result is a simple, low-cost, and potentially low-power RF ranging system that requires very little digital signal processing.

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Mutual interference of pseudorandom noise radar in automotive collision avoidance application at 24 GHz

Cited by 10 publications

References 6 publications

Geometric Sequence Decomposition-Based Interference Cancellation in Automotive Radar Systems

Geometric Sequence Decomposition-Based Interference Cancellation in Automotive Radar Systems

Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences

Generating and Detecting Solvable Chaos at Radio Frequencies with Consideration to Multi-User Ranging

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