This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for radio frequency (RF) sensing in the millimeter-wave frequency spectrum that can be performed over multiple phases. During a session setup phase, a radar initiator identifies one or more wireless stations (STAs) that are capable of radar ranging and sets up a radar measurement session that includes at least one of the identified STAs. During a measurement negotiation phase, the radar initiator performs a respective beamforming training operation with each STA and indicates, to each STA, one or more parameters associated with the radar measurement session. During a radar measurement phase, the radar initiator transmits radar setup information to, and receives ranging information from, each STA. In some aspects, the radar initiator may perform an object detection operation that indicates a location of an object associated with the ranging information received from each radar STA.

An estimated initial direction of movement of a newly-detected object is to be determined. The actual previous directions of movement and positions of previously-detected objects are determined and stored. When a newly-detected object is newly detected at a certain position, then the actual previous direction of movement of one of the previously-detected objects at that position is used as a basis to determine the estimated initial direction of movement of the newly-detected object at that position.

An example method includes gathering, via a first module of a first type, first simultaneous localization and mapping data and gathering, via a second module of a second type, second simultaneous localization and mapping data. The method includes generating, via a simultaneous localization and mapping module, a first map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the first map being of a first map type and generating, via the simultaneous localization and mapping module, a second map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the second map being of a second map type. The map of the first type is used by vehicles with module(s) of the first and/or second types and the map of the second type is used by vehicles with a module of the second type exclusively.

A method and an apparatus for obtaining information are disclosed. The method includes: determining that a first sensor in environment sensing sensors in a vehicle fails; determining a first detection area of the first sensor, where the first detection area includes a first angle range, and the first angle range is an angle range of a detection angle, of the first sensor, that covers a driving environment around the vehicle; adjusting a second detection area of a dynamic sensor in the vehicle, so that an angle range of the second detection area covers the first angle range, where the angle range of the second detection area is a range of a detection angle, of the dynamic sensor, that covers a driving environment around the vehicle; and obtaining environment information by using the dynamic sensor.

A method may include obtaining first sensor data from a first sensor system and second sensor data from a second sensor system. The first and the second sensor systems may capture sensor data from a total measurable world. The method may include identifying a first object included in the first sensor data and a second object included in the second sensor data and determining first parameters corresponding to the first object and second parameters corresponding to the second object. The first parameters may be compared with the second parameters and whether the first object and the second object are a same object may be determined based on the comparing the first parameters and the second parameters. Responsive to determining that the first object and the second object are the same object, a set of objects representative of objects in the total measurable world including the same object may be generated.

A communication device includes a target locating unit configured to locate a position of a target having a risk of approaching a moving body. The communication device includes a transmission unit configured to transmit request information including positional information of an external terminal, for which the positional information is requested, based on the position of the target located by the target locating unit. The communication device includes a reception unit configured to receive response information with respect to the request information. The transmission unit is configured to transmit warning information based on the positional information of the external terminal included in the response information.

A sensor calibration method and apparatus, and a storage medium are provided. In the method, multiple scene images and multiple first point clouds of a target scene are acquired by an image sensor and a radar sensor. A second point cloud of the target scene is constructed according to the multiple scene images. A first distance error between the image sensor and radar sensor is determined according to first feature point sets and a second feature point set. A second distance error of the radar sensor is determined according to multiple first feature point sets. A reprojection error of the image sensor is determined according to a first global position of the second feature point set in the global coordinate system and first image positions of pixel points corresponding to the second feature point set in the scene image. The radar sensor and image sensor are calibrated.

To provide a precipitation particle classification apparatus for obtaining a proper classification result of precipitation particles based on information from a plurality of radar devices. The precipitation particle classification apparatus includes a data processing part, a fuzzy processing part, a coordinate conversion part, an interpolation part, and a classification part. The data processing part acquires polarization parameters obtained by reflection on the precipitation particles from each of the plurality of radar devices which are arranged at different positions and have a part of a scanning area overlapping with each other. The fuzzy processing part obtains a polar coordinate distribution evaluation value indicating the distribution in polar coordinates of an evaluation value indicating the degree of attribution to each type of precipitation particles from polarization parameters by using a fuzzy inference. The coordinate conversion part converts the polar coordinate distribution evaluation value into the Cartesian coordinate distribution evaluation value. The interpolation part integrates the Cartesian coordinate distribution evaluation values whose positions on the coordinates are substantially equal among the Cartesian coordinate distribution evaluation values obtained for each of the plurality of radar devices to obtain a composite evaluation value. The classification part classifies precipitation particle species based on the composite evaluation value.

A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

A method may include obtaining first sensor data from a first sensor system and second sensor data from a second sensor system. The first and the second sensor systems may capture sensor data from a total measurable world. The method may include identifying a first object included in the first sensor data and a second object included in the second sensor data and determining first parameters corresponding to the first object and second parameters corresponding to the second object. The first parameters may be compared with the second parameters and whether the first object and the second object are a same object may be determined based on the comparing the first parameters and the second parameters. Responsive to determining that the first object and the second object are the same object, a set of objects representative of objects in the total measurable world including the same object may be generated.