Embodiments are directed to a dynamic radar detection threshold for stateful dynamic frequency selection (DFS). An embodiment of a storage medium includes instructions to operations including estimate a duty time of transmission of wireless signals by an access point, the access point to provide Wi-Fi communication, the wireless signals being communicated on a DFS channel of the access point, adapt, based at least in part on the duty time of transmission, a threshold of radar signals to indicate detection of a radar signal at the access point on the DFS channel, and perform analysis of received wireless signals on the DFS channel at the access point to detect the radar signal using the adapted threshold of radar signals.

This document describes techniques, apparatuses, and systems for radar interference mitigation using signal pattern matching. Radar signals (e.g., chirps) received by a radar system may include interference from other nearby radar systems. The interference can result in reduced sensitivity of the radar system. The techniques, apparatuses, and systems described herein mitigate the interference by selecting an uncorrupted segment of the radar signal that neighbors a corrupted segment, analyzing the radar signal to identify a match segment that has similar signal characteristics to the neighbor segment, and replacing the corrupted segment with a segment that is adjacent to the match segment. In this manner, a noise floor of the radar system may be lowered, leading to increased sensitivity.

A reflectivity correction method using a double polarization variable-based bright band detection result includes a preprocessing operation for correcting a double polarization variable observation error and calculating a depolarization ratio; a fuzzy classifier generation operation for calculating a weighting and a membership function of each characteristic variable using a bright band height extracted from a quasi-vertical profile generated from specific elevation angle data, a bright band detection operation for detecting a bright band using a depolarization ratio and a fuzzy classifier for each elevation angle, and a reflectivity correction operation for correcting reflectivity over-observation for a detected bright band region on the basis of a correction factor calculated using an apparent profile of reflectivity generated by averaging reflectivity data for the bright band region for each elevation angle. Thus, it is possible to improve the accuracy of precipitation estimation by using the corrected reflectivity.

An object detection method includes: obtaining a first offset value and a second offset value, setting a first detection threshold value by adding the first offset value to a first reference threshold value, setting a second detection threshold value by adding the second offset value to a second reference threshold value, obtaining a detection input, and performing target detection upon the detection input according to at least the first detection threshold value and the second detection threshold value. The first offset value is different from the second offset value. The first reference threshold value is determined for detecting if at least one object with a first value of an object characteristic exists. The second reference threshold value is determined for detecting if at least one object with a second value of the object characteristic exists. The second value is different from the first value.

A snapshot comprises a plurality of signals is received where each of the plurality of signals reflected from a respective source and received by an antenna array. A first DoA estimator determines, based on the received snapshot, a plurality of DoAs, the plurality of DoAs comprising a respective DoA for each of the plurality of signals. A reliability of the plurality of DoAs is measured. In response to the reliability of the plurality of the DoAs exceeding a threshold, at least one of the plurality of the DoAs determined by the first DoA estimator is output. In response to the reliability of the plurality of the DoAs not exceeding the threshold, a second DoA estimator determines based on the received snapshot a second plurality of DoAs comprising a respective DoA of each of the plurality of signals and outputs at least one of the second plurality of DoAs.

In one embodiment, a method includes receiving a first signal associated with a first multipath effect from a first radar installed on a vehicle at a first height, receiving a second signal associated with a second multipath effect from a second radar installed on the vehicle at a second height, wherein the first height and the second height are different, wherein a difference between the first height and the second height is configured to generate a mitigation of the first multipath effect and the second multipath effect, and wherein the first radar and the second radar have an overlapping field of view, and determining that a target exists in the overlapping field of view based on the first signal and the second signal.

Example embodiments relate to techniques for detecting adverse road conditions using radar. A computing device may generate a first radar representation that represents a field of view for a radar unit coupled to a vehicle and during clear weather conditions and store the first radar representation in memory. The computing device may receive radar data from the radar unit during navigation of the vehicle on a road and determine a second radar representation based on the radar data. The computing device may also perform a comparison between the first radar representation and the second radar representation and determine a road condition for the road based on the comparison. The road condition may represent a quantity of precipitation located on the road and provide control instructions to the vehicle based on the road condition for the road.

Disclosed are systems that include a controller circuit in communication with a ranging sensor configured to detect objects proximate to a host vehicle. In an aspect, the controller circuit is configured to perform a first detection count of the detected objects, determine a first group of objects of the detected objects, determine a first distance to the first group of objects, utilize the first distance to determine a trailer distance between the host vehicle and a front of a trailer, determine a second group of objects of the detected objects, determine a second distance to the second group of objects, utilize the second distance to determine an axle distance between the front of the trailer and a trailer axle, and determine a trailer length based on the trailer distance and the axle distance. Methods are also disclosed.

The present invention relates to radar systems and methods of using same that are more efficient than current radar systems and methods of using same. Such radar systems and methods of using same using employs a plurality of pluses is used to make a decision on the presence or absence of a target. Such radar system and method of using same is more efficient as the position and velocity of a potential target is carried over from pulse burst to pulse burst. Thus, the radar signal structure from the target is the same, which in turn results in a high cross correlation that can used to efficiently decide if signal return is from an actual target or is due to interference.

A method (100; 200) for digital signal processing (S(t)) of a pulse and scanning radar during an observation of a coastal zone in land/sea detection mode, the signal being sampled according to a two-dimensional temporal map, a distance dimension (d) and a recurrence dimension (rec), comprising: selecting a digital terrain model file (MNT) of the observed coastal zone; transforming (110; 210) the temporal map and/or the digital terrain model file to obtain a transformed temporal map and/or a transformed digital terrain model file the data of which are expressed in a common reference frame; constructing (120) a mask (MT; MF) from the transformed digital terrain model file; and applying (130) the mask to the samples (E(d, rec); E(d, Δf)) of the map associated with the transformed temporal map, in such a way as to obtain filtered samples (Ef(d, rec); Ef(d, Δf)).