Search results for "Angle of arrival"
showing 3 items of 13 documents
An ergodic wideband MIMO channel simulator based on the geometrical T-junction scattering model for vehicle-to-vehicle communications
2010
In this paper, a wideband multiple-input multiple-output (MIMO) simulation model for vehicle-to-vehicle (V2V) channels in T-junction propagation environments is proposed. This simulation model takes the exact relationship between the angle-of-arrival (AOA) and the angle-of-departure (AOD) into account. In order to determine the parameters of the simulation model, the Riemann sum method (RSM) is applied. Furthermore, the statistical and ergodic properties of the simulation model are studied. Closed-form solutions are derived for the space-time-frequency cross-correlation function (STF-CCF), the two-dimensional (2D) spatial cross-correlation function (CCF), the temporal autocorrelation functi…
Localization of Multi-Class On-Road and Aerial Targets Using mmWave FMCW Radar
2021
mmWave radars play a vital role in autonomous systems, such as unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), ground station control and monitoring systems. The challenging task when using mmWave radars is to estimate the accurate angle of arrival (AoA) of the targets, due to the limited number of receivers. In this paper, we present a novel AoA estimation technique, using mmWave FMCW radars operating in the frequency range 77–81 GHz by utilizing the mechanical rotation. Rotating the radar also increases the field of view in both azimuth and elevation. The proposed method estimates the AoA of the targets, using only a single transmitter and receiver. The measurements are…
Classification of Targets Using Statistical Features from Range FFT of mmWave FMCW Radars
2021
Radars with mmWave frequency modulated continuous wave (FMCW) technology accurately estimate the range and velocity of targets in their field of view (FoV). The targeted angle of arrival (AoA) estimation can be improved by increasing receiving antennas or by using multiple-input multiple-output (MIMO). However, obtaining target features such as target type remains challenging. In this paper, we present a novel target classification method based on machine learning and features extracted from a range fast Fourier transform (FFT) profile by using mmWave FMCW radars operating in the frequency range of 77–81 GHz. The measurements are carried out in a variety of realistic situations, including p…