A millimeter-wave automotive radar with high angular resolution for identification of closely spaced on-road obstacles

Abstract

Frequency-modulated continuous wave radar techniques typically have inadequate angular resolutions due to the limited aperture sizes of antenna arrays in spite of employing multiple-input multiple-output (MIMO) techniques. Therefore, despite the existence of multiple objects, angularly close objects with similar distances and relative velocities are recognized as one single object. Autonomous driving requires the accurate recognition of road conditions. This requirement is one of the critical issues to be solved to distinguish significantly close objects. This paper proposes a technique referred to as an antenna element space pseudo-peak suppressing (APPS) method to resolve angularly close targets. The proposed APPS method aims to identify closely spaced objects on roads. These angularly close targets cause a single peak in a spatial spectrum obtained by a beamformer-based angle estimation. The APPS considers this single peak as pseudo. The APPS radar cancels this pseudo peak from the spatial spectrum. Then, the obtained residual received signal is analyzed. With these procedures, the APPS identifies the number of targets. The APPS also estimates the target angles. The proposed APPS is experimentally validated using a typical single-chip MIMO-based radar evaluation board with three transmit (TX) and four receive (RX) antennas. The experimental results confirm that the proposed APPS successfully resolves angularly close pseudo targets with an angle difference of approximately $$0.5^\circ $$ 0 . 5 ∘ .

Integration of MoS2 Memtransistor Devices and Analogue Circuits for Sensor Fusion in Autonomous Vehicle Target Localization

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Height detection of crop divider toes of sugarcane harvester based on Kalman adaptive adjustment

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