A multisensor data fusion perception method includes receiving feature data from a plurality of types of sensors, obtaining static feature data and dynamic feature data from the feature data, constructing current static environment information based on the static feature data and reference dynamic target information, and constructing current dynamic target information based on the dynamic feature data and reference static environment information such that construction of a dynamic target and construction of a static environment are performed by referring to each other's construction results and the perception capability is for the dynamic target and the static environment that are in an environment in which the moving carrier is located.

Method and apparatus are disclosed for communication of infrastructure information to a vehicle via ground penetrating radar. A vehicle comprising an antenna positioned to broadcast radio waves below the vehicle, a ground penetrating radar system, and an active safety module. The ground penetrating radar system determines types of reflectors and a spatial relationship between the reflectors based on radar cross-sections detected by the antenna, and generates a signature based on the shapes and the spatial relationship. The active safety module determines environmental data based on the signature, and autonomously control the vehicle based on the environmental data.

Method and apparatus are disclosed for communication of infrastructure information to a vehicle via ground penetrating radar. A vehicle comprising an antenna positioned to broadcast radio waves below the vehicle, a ground penetrating radar system, and an active safety module. The ground penetrating radar system determines types of reflectors and a spatial relationship between the reflectors based on radar cross-sections detected by the antenna, and generates a signature based on the shapes and the spatial relationship. The active safety module determines environmental data based on the signature, and autonomously control the vehicle based on the environmental data.

In some embodiments, a non-transitory computer-readable storage medium includes instructions to identify, based upon Doppler-speed determination from one or more radars, radar targets within a hitbox for determining a first stationary status of a vehicle based on tracking Doppler-speed radar targets in a hitbox region. The medium also includes instructions to identify, based upon the Doppler speed determination from the one or more radars, field-of-view (FOV) radar targets for determining a second stationary status based on a substantial number and a distribution of Doppler-speed determinations for the FOV radar targets. The medium also includes instructions to confirm, based on detecting a change in either of the first or the second stationary status of the vehicle, an acceleration sensed by an inertial measurement unit onboard the vehicle.

A system for determining a stationary state of a rail vehicle on a track includes a first radar mounted at an end of the rail vehicle and a second radar mounted at another end of the rail vehicle. A speed sensor is mounted on the rail vehicle. A series of fixed reflective track features are found along the track. A processing unit, communicably connected with the speed sensor, the first radar and the second radar receives data from the first radar and the second radar corresponding to the distance to the fixed reflective track features and determines the stationary state or low-speed condition of the rail vehicle and checks the state or condition by comparing it with an output of the speed sensor.

A method and a device for determining the position of a vehicle, said method comprising the steps: recording sensor data from the ground over which the vehicle travels; extracting ground characteristics of the ground over which the vehicle travels from the recorded sensor data or from occupancy grids which are calculated on the basis of the sensor data; determining the current position of the vehicle on the basis of the extracted ground characteristics using a characteristic map.

Device for determining the mixing ratio of a mixture of at least two different fluids, the device comprising: a pipe section with a measuring region; wherein the mixture flows through the measuring region; a radar sensor system with a radar sensor chip arranged on an outer wall of the pipe section. The radar sensor system is configured to: irradiate frequency-modulated millimeter-radar waves (f.sub.S) in a specified frequency range (f) into the measuring region; receive millimeter-radar waves (f.sub.R) backscattered by the mixture; determine a frequency-dependent reflection coefficient (.sub.f) for the specified frequency range (f) using the backscattered millimeter-radar waves (f.sub.R); and calculate or allocate the mixing ratio from the determined frequency-dependent reflection coefficient (.sub.f).

An FMWC radar sensor for motor vehicles, having a high-frequency oscillator, which is developed to generate a frequency-modulated transmit signal that has a periodically repeating series of modulation sequences having different modulation patterns, and having an evaluation device for evaluating the received radar echo according to the FMCW principle, wherein the series of the modulation sequences includes a special class of modulation sequences whose duration is longer than that of any other modulation sequence not belonging to this class and whose frequency swing is smaller than that of any other modulation sequence, and the evaluation device is developed to carry out a measurement of the ego velocity of the vehicle on the basis of a radar echo that is received from non-moving objects during the modulation sequences that belong to the special class.

Systems, methods, and non-transitory computer-readable media can receive data captured by a radar system on a vehicle. A curve is determined based on the data. A speed estimate for the vehicle is generated based on the curve.

Deep learning to improve or gauge the performance of a surface-penetrating radar (SPR) system for localization or navigation. A vehicle may employ a terrain monitoring system including SPR for obtaining SPR signals as the vehicle travels along a route. An on-board computer including a processor and electronically stored instructions, executable by the processor, may analyze the acquired SPR images and computationally identify subsurface structures therein by using the acquired image as input to a predictor that has been computationally trained to identify subsurface structures in SPR images.