A study of compressed sensing based collision avoidance by multi-sensor CW radar data

Azodi, Hossein; Siart, Uwe; Eibert, Thomas F.

doi:10.1109/eurad.2014.6991259

Cited by 2 publications

(1 citation statement)

References 13 publications

(15 reference statements)

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“…Millimeter-wave radars, [28][29][30] by contrast, is relatively less expensive, is not easily influenced by environmental elements, and has precision; thus, they are suitable for use in CAA systems. 32 Radar cross-section, multi-target recognition, wave studies, signal processing, and transceiver isolation are essential technologies in millimeter-wave radar sensing. The electromagnetic compatibility and space electromagnetic interference of radars and other hardware systems 33,34 must be reviewed.…”

Section: Environment Perceptionmentioning

confidence: 99%

A review of essential technologies for collision avoidance assistance systems

Zhao

Zhou

Zhu

et al. 2017

Advances in Mechanical Engineering

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Compared with automatic collision avoidance systems, collision avoidance assistance systems have attracted more research interest because they help avoid collisions in near-accident situations. However, ensuring the robustness and reliability of collision avoidance assistances is difficult because of problems in reliable environment recognition, accurate collision avoidance decision making, and driver acceptance. This article reviews and analyzes three essential technologies for collision avoidance assistance systems in intelligent environment-friendly vehicles. The architecture of the human-inloop system is summarized, and available environment recognition methods used in collision avoidance assistances are compared. Moreover, the characteristics of path planning and collision avoidance decision making applied in emergency collision avoidance assistance systems are reviewed, and the advantages of applying haptic share control and yaw moment active intervention during path tracking are analyzed. The emergency collision avoidance assistance systems based on driver behavior models and HSC were found to be the most suitable for high-speed emergency conditions. Such systems are not only highly robust but also more likely to be accepted by drivers.

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Section: Environment Perceptionmentioning

confidence: 99%

A review of essential technologies for collision avoidance assistance systems

Zhao

Zhou

Zhu

et al. 2017

Advances in Mechanical Engineering

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Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar

et al. 2016

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Abstract. A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The underlying sensor platform consists of several homodyne continuous wave (CW) radar modules. Based on In-phase-Quadrature (IQ) processing and down-conversion, they provide only Doppler shift information about the observed target. Localization with Doppler shift estimates is a nonlinear problem that needs to be linearized before the linear KF can be applied. The accuracy of state estimation depends highly on the introduced linearization errors, the initialization and the models that represent the true physics as well as the stochastic properties. The important issue of filter consistency is addressed and an initialization procedure based on data fitting and maximum likelihood estimation is suggested. Models for both, measurement and process noise are developed. Tracking results from typical three-dimensional courses of movement at short distances in front of a multi-sensor radar platform are presented.

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A study of compressed sensing based collision avoidance by multi-sensor CW radar data

Cited by 2 publications

References 13 publications

A review of essential technologies for collision avoidance assistance systems

A review of essential technologies for collision avoidance assistance systems

Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar

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