Systems and methods for detecting and tracking objects using radar data are disclosed. The methods include receiving measurement data corresponding to an environment of a vehicle from a radar sensor associated with the vehicle, and identifying one or more object tracks of a plurality of object tracks that lie within an extended field of view (FOV) of the radar sensor. The extended FOV may be determined based on an original FOV of the radar sensor. The methods further include performing association of the measurement data with the one or more object tracks to identify an associated object track, and outputting the associated object track and the measurement data to a navigation system of the vehicle.

A circuit includes a signal processing unit to generate a radar map represented by an array with a first index and a second index, and a peak detection unit to identify potential targets in the radar map. Within the peak detection unit, a first peak detection sub-unit scans the radar map along the first index and stores a first detection bitmap that identifies peaks as a function of the first index, and a second peak detection sub-unit scans the radar map along the second index and outputs a second detection bitmap that identifies peaks as a function of the second index. The first detection bitmap and the second detection bitmap identify the peaks using a single bit. A hardware accelerator processes individual bits of the first detection bitmap and of the second detection bitmap.

Methods, systems, and devices for wireless communications are described. A user equipment (UE), such as a vehicle that is enabled with radar detection and ranging, may include multiple radars or radar components and may receive, at a first radar, a first radar waveform in a field of view (FOV) associated with the first radar. The UE may determine a trajectory of the target object which may indicate the target object entering a FOV of a second radar. The UE may receive, at the second radar, a second radar waveform in the FOV of the second radar and may associate the second radar waveform with the target object based on the trajectory of the target object and the second radar waveform being in the FOV of the second radar.

The disclosure includes a computer-implemented method for predicting trajectory data of an object including: acquiring radar data of the object; determining a parametrization of the trajectory data of the object based on the radar data; and determining a variance of the trajectory data of the object based on the radar data. The trajectory data of the object includes a position of the object and a direction of the object. The parametrization includes a plurality of parameters and a polynomial of a pre-determined degree. The parameters include a plurality of coefficients related to elements of a basis of the polynomial space of polynomials of the pre-determined degree.

A a method for managing a secondary radar operating in Mode S, the method includes a) a detection in “seeking mode”, the “seeking mode” being implemented until an aircraft is detected by the secondary radar; b) a detection in “tracking mode”, the “tracking mode” being implemented if a valid response to a roll-call interrogation was detected in “seeking mode”; the method comprising an intermediate step a1), which is executed between the detection in “seeking mode” and the detection in “tracking mode”, the intermediate step comprising: detecting the presence or absence of the reply of the aircraft in a noise window of the secondary radar; carrying out at least one roll-call interrogation, using the first monitoring window, if the reply of the aircraft is not located in the noise window.

A radar apparatus for a vehicle includes radar sensors, and a controller configured to generate information on the object based on a radar signal reflected by the object entering the fields of sensing of the radar sensors, wherein the controller, when the object is duplicately detected by two or more of the radar sensors, integrates two or more pieces of information on the objects detected by the two or more radar sensors, respectively, into one, and when the object moves from a field of sensing of a first radar sensor to a field of sensing of a second radar sensor, performs control to hand over the information on the object between the first radar sensor and the second radar sensor. Accordingly, information on an object detected by a radar sensor can be efficiently processed and an object moving through fields of sensing of radar sensors can be continuously detected.

There are provided an object recognition apparatus that raises the recognition accuracy for a surrounding object and a vehicle control apparatus, and an object recognition method and a vehicle control method. An object recognition apparatus receives object data, which is a state value of the object, from a first sensor for detecting a surrounding object; compares estimation data obtained through estimation of a state value of the object, based on recognition data calculated in a past period, with the object data, and determines whether or not the object data is data in a low-resolution state; then, in accordance with the determination result, calculates the state value of the object by use of object data and estimation data and then generates the state value as recognition data, so that the recognition accuracy for an object is raised.

An edge device includes a first antenna array and a sensor that senses a surrounding area of the edge device. The edge device further includes control circuitry that detects a first user in the surrounding area of the edge device sensed by the sensor. The control circuitry tracks the detected first user in the surrounding area of the edge device based on the sensor and control the first antenna array to direct a first beam of radio frequency (RF) signal having a signal strength greater than a first threshold in a first direction of the first user being tracked based on the sensor for high-performance communication.

Methods, systems, and products for resolving level ambiguity for radar systems of autonomous vehicles may include detecting a plurality of objects with a radar system. Each first detected object may be associated with an existing tracked object based on a first position thereof. First tracked object data based on a first height determined for each first detected object may be stored. The first height may be based on the position of the detected object, the existing tracked object, and a tile map. Second tracked object data based on a second height determined for each second detected object not associated with the existing tracked object(s) may be stored. The second height may be based on a position of each second detected object, a vector map, and the tile map. A command to cause the autonomous vehicle to perform at least one autonomous driving operation may be issued.

Disclosed is a technique for processing signals received from a radar and, in particular, a technique for tracking a target on the basis of detected target candidate signals. The proposed invention introduces a recurrent neural network with a memory function in order to find a target signal from signals with noise and fake signals mixed therein. This recurrent neural network is trained to have a maximum of Q tracking buffers therein. According to an additional aspect, it is possible to increase tracking accuracy through a serial connection of the recurrent neural network. According to an additional aspect, it is possible to track multiple targets through a parallel connection of the recurrent neural network.