Estimation on Location, Velocity, and Acceleration With High Precision for Collision Avoidance

Tu, Po-Jen; Kiang, Jean‐Fu

doi:10.1109/tits.2010.2043098

Cited by 21 publications

(2 citation statements)

References 12 publications

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“…After mixing with the transmitted signal and filtering the echo signal, the beat frequency signal can be obtained, and the target information can be obtained by processing the beat frequency signal. FMCW radar basically has three main waveforms: fast ramp wave, triangular wave and trapezoidal wave [5][6][7] . The fast sawtooth wave has better performance by using twodimensional FFT scheme in multi-object scene, and it is easy to realize processing.…”

Section: Introductionmentioning

confidence: 99%

Multi-targets detection using 3D-FFT scheme for TDM-MIMO automotive radar

Tian¹,

Jiang²,

Yang³

2023

Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022)

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Automotive radar is the key component of driver assistance system. The main current requirements of are high angular resolution, high target detection accuracy, low power consumption, and low cost. However, ambiguous target and low angle measurement accuracy will appear in the multi-target scenario. In order to solve these problems, TDM-MIMO (time division multiplexing multiple-input-multiple-output) radar is implemented to improve the angular resolution. We use the proposed TDM-MIMO LFMCW (linear frequency modulated continuous wave) echo model to derive the range, velocity and azimuth information of the target. And we present a 3D-FFT (three-dimensional fast Fourier transform) scheme to solve the problem of multi-target detection. In the simulation, we effectively solve the accuracy problem in multi-target detection without ambiguity, and the angular resolution is improved by about 14°.

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Section: Introductionmentioning

confidence: 99%

Multi-targets detection using 3D-FFT scheme for TDM-MIMO automotive radar

Tian¹,

Jiang²,

Yang³

2023

Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022)

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show abstract

“…The past two decades have witnessed a boom in the use of positioning technologies in various vehicle guidance-and safetyrelated applications, which typically include route guidance, emergency assistance, freight management, collision avoidance, electronic fee collection, etc [1][2][3]. With the further development of intelligent transportation system (ITS), accurate, reliable and continuous vehicle positioning at an affordable cost is of vital importance and has drawn global attention [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A novel fusion methodology to bridge GPS outages for land vehicle positioning

Chen

Liu

Song

et al. 2015

Meas. Sci. Technol.

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Many intelligent transportation system applications require accurate, reliable, and continuous vehicle position information whether in open-sky environments or in Global Positioning System (GPS) denied environments. However, there remains a challenging task for land vehicles to achieve such positioning performance using low-cost sensors, especially microelectromechanical system (MEMS) sensors. In this paper, a novel and cost-effective fusion methodology to bridge GPS outages is proposed and applied in the Inertial Navigation System (INS)/GPS/ compass integrated positioning system. In the implementation of the proposed methodology, a key data preprocessing algorithm is first developed to eliminate the noise in inertial sensors in order to provide more accurate information for subsequent modeling. Then, a novel hybrid strategy incorporating the designed autoregressive model (AR model)-based forward estimator (ARFE) with Kalman filter (KF) is presented to predict the INS position errors during GPS outages. To verify the feasibility and effectiveness of the proposed methodology, real road tests with various scenarios were performed. The proposed methodology illustrates significant improvement in positioning accuracy during GPS outages.

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Model-based and model-free collision detection and identification for a parallel Delta robot with uncertainties

Pham,

Kuo

2023

Control Engineering Practice

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Estimation on Location, Velocity, and Acceleration With High Precision for Collision Avoidance

Cited by 21 publications

References 12 publications

Multi-targets detection using 3D-FFT scheme for TDM-MIMO automotive radar

Multi-targets detection using 3D-FFT scheme for TDM-MIMO automotive radar

A novel fusion methodology to bridge GPS outages for land vehicle positioning

Model-based and model-free collision detection and identification for a parallel Delta robot with uncertainties

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