BACKGROUND

Aspects of the present disclosure relate generally to radar, and more particularly, to beamforming for radar.

Multi-antenna radar systems can broadly be classified into two categories: phased arrays radars, in which phase-shifted versions of the same signal are emitted from the antennas, and multiple-input, multiple-output (MIMO) radar, in which general signals can be emitted from the antennas. The increased adaptability of MIMO radar offers significant advantages over phased-array radar, including increased identifiability and flexibility in transmit beam pattern design.

A number of prior works have studied the problem of designing emitted signals for MIMO radar systems to create desired transmit beam patterns. The methods described in the prior works vary in the amount of prior target information obtained from track filters at the receiver utilized to create the desired transmit beam patterns. Some methods do not use any prior target information and focus on creating beam patterns with wide coverage. Some methods create beam patterns adapted to the tracked azimuth angles to the targets. One such method designs the beam pattern using a two step-process, which first selects a cross-correlation matrix to achieve a desired beam pattern and then chooses signals having that correlation. This two-step process couples the design of the spatial and temporal signal dimensions. Another method decouples the spatial and temporal dimensions of the beamforming design. Another class of methods adopts a beam-space approach to beamformer designs, which aims to combine the benefits of phased-array and MIMO radar. For example, subarrays may be separately designed such that each subarray acts as a phased array. Another approach limits sidelobes within tolerable levels in prescribed regions. Beamformer designs may also address mismatches between the presumed and actual beamforming vectors.

In the automotive context, beamforming has also been studied from the perspective of interference avoidance. A few recently proposed methods have adapted beam patterns for improved detection. Some methods focus on adapting waveforms to account for change in clutter in the radar scene, while other methods focus on adaptive beamforming to improve tracking. One proposal is to sequentially adapt the beam pattern to improve the conditional Bayesian Cramer-Rao bound in a single target tracking problem. Adaptive beamforming schemes may also be applied to multiple target tracking.

The different beamforming methods described above either implicitly or explicitly assume that the data association problem can be solved without errors (i.e., detections can correctly be associated to targets). Beamforming patterns are designed to maximize detection and estimation accuracy under this assumption. This association, however, may not always be true. Thus, improvements in radar beamforming may be desired.

SUMMARY

The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

In an aspect, the present disclosure includes a method of radar detection. The method may include obtaining prior information about known targets including an azimuth angle of each known target. The method may include generating an association aware transmit beam pattern toward at least a subset of the known targets based on the prior information. The method may include detecting targets from reflected beams of the association aware transmit beam pattern.

In another aspect, the disclosure provides a radar including a plurality of antennas, a memory storing executable instructions, and a processor communicatively coupled with the plurality of antennas and with the memory. The processor may be configured to obtain prior information about known targets including an azimuth angle of each known target. The processor may be configured to generate an association aware transmit beam pattern toward at least a subset of the known targets based on the prior information. The processor may be configured to detect targets from reflected beams of the association aware transmit beam pattern.

In another aspect, the disclosure provides a radar including means for obtaining prior information about known targets including an azimuth angle of each known target. The radar may include means for generating an association aware transmit beam pattern toward at least a subset of the known targets based on the prior information. The radar may include means for detecting targets from reflected beams of the association aware transmit beam pattern.

In another aspect, the disclosure provides a computer-readable medium storing instructions executable by a processor of a radar device. The computer-readable medium may include code for obtaining prior information about known targets including an azimuth angle of each known target. The computer-readable medium may include code for generating an association aware transmit beam pattern toward at least a subset of the known targets based on the prior information. The computer-readable medium may include code for detecting targets from reflected beams of the association aware transmit beam pattern.

To the accomplishment of the foregoing and related ends, the one or more aspects comprise the features hereinafter fully described and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative features of the one or more aspects. These features are indicative, however, of but a few of the various ways in which the principles of various aspects may be employed, and this description is intended to include all such aspects and their equivalents.

