Sequential Doppler Focusing Radar for Autonomous Vehicles
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Solution Overview
Problem
Autonomous vehicles face challenges in determining the velocity of objects in their surroundings with high accuracy due to limited computational and power resources, which affects object detection and trajectory prediction.
Innovation Solution
The use of different tiers of radar pulses, including low-resolution Doppler measurements to identify frequency bins corresponding to agents, followed by high-resolution processing only on those bins, minimizes power consumption and computational burden while achieving precise Doppler measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution Doppler measurements are performed on all frequency bins, then velocity measurement precision is improved, but computational burden and power consumption increase significantly
Solution Approach 1:
The patent segments the frequency bins into two categories: bins corresponding to detected objects and bins not corresponding to objects. High-resolution Doppler processing is applied only to the segmented object-related bins, while non-object bins receive low-resolution processing. This segmentation resolves the contradiction by limiting complex computations to only where high precision is needed.
Solution Approach 2:
The patent applies different processing qualities to different frequency bins based on local needs. Object-related bins receive high-resolution Doppler processing for accurate velocity measurement, while non-object bins receive low-resolution processing. This local differentiation maintains measurement precision for objects while reducing overall computational burden.
2Measurement precision
If high-resolution Doppler measurements are performed on all frequency bins, then velocity measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent segments frequency bins based on object detection results, applying high-resolution processing only to the necessary subset of bins related to detected objects. This segmentation strategy reduces the total number of high-resolution computations, thereby lowering power consumption while maintaining velocity measurement precision for objects of interest.
Solution Approach 2:
The patent performs high-resolution Doppler processing partially - only on frequency bins corresponding to detected objects rather than on all bins. This partial action approach provides sufficient velocity measurement precision for objects while avoiding the excessive power consumption that would result from processing all bins at high resolution.
3Use of energy by moving object
If low pulse repetition frequency is used, then power consumption is reduced, but Doppler measurement resolution deteriorates
Solution Approach 1:
The patent dynamically adjusts the pulse repetition frequency based on the processing mode. During low-resolution scanning of all frequency bins, a lower PRF is used to reduce power consumption. When high-resolution Doppler processing is applied to object-related bins, the PRF is increased to achieve the necessary measurement resolution. This dynamic adjustment resolves the contradiction between power consumption and measurement resolution.
4Productivity
If comprehensive radar scanning of all frequency bins is performed, then object detection coverage is improved, but processing time increases
Solution Approach 1:
The patent segments the frequency bin processing into two phases: a comprehensive low-resolution scanning phase that covers all bins for initial object detection, followed by a focused high-resolution phase that processes only object-related bins. This segmentation improves overall productivity by quickly identifying objects while reducing processing time through selective detailed analysis.
Solution Approach 2:
The patent performs preliminary low-resolution scanning of all frequency bins to identify object locations before conducting high-resolution Doppler processing. This preliminary action ensures comprehensive object detection coverage while minimizing processing time by avoiding immediate high-resolution processing of all bins.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate object detection and trajectory prediction with reduced power and computational costs, optimizing radar system efficiency in autonomous vehicles.
Implementation Method 1
the first value corresponds to a Doppler frequency shift value determined from a first reflected wave reflected from the object
Implementation Method 2
A radar system determines a velocity of an object
Data Source
AI summary
In one embodiment, a method includes configuring a radar transceiver to transmit a first number of radar pulses at a first pulse repetition frequency (PRF); and determining a first value corresponding to a first object based on a first radar data received in response to the first number of radar pulses. The first object is identified based on the first value being higher than a predetermined threshold value. The method also includes configuring the radar transceiver to transmit a second number of radar pulses at a second PRF that is higher than the first PRF; determining a second value of the first object based on a second radar data received in response to the second number of radar pulses; and associating the second value with information of the first object.