Single-Radar Localization Using Doppler Arrays for Low-Latency Mapping
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Solution Overview
Problem
Traditional radar-based localization and mapping methods are limited by accuracy and latency, requiring multiple sensors and relying solely on Doppler information from stationary objects, which restricts the precision and efficiency of determining sensor platform motion.
Innovation Solution
A system and method utilizing a single radar sensor with advanced AI techniques, incorporating transmitter and receiver arrays, and optional auxiliary sensors to enhance localization and mapping processes, enabling precise determination of motion and environment mapping using radar data alone or in combination with other sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple radar sensors are used to determine motion, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the radar sensor into multiple transmitter and receiver arrays, where each array can independently process Doppler information. This allows a single physical sensor to provide multiple measurement dimensions, achieving the precision of multiple sensors without the complexity of deploying multiple complete sensor systems.
Solution Approach 2:
The patent introduces spatial dimensionality by using multiple transmitter and receiver arrays arranged in specific geometries. This creates additional measurement dimensions from a single sensor, enabling the system to determine motion parameters that would otherwise require multiple separate sensors.
2Measurement precision
If Doppler information from stationary objects is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary processing of radar returns to identify and classify stationary objects before motion determination. This preliminary action filters out irrelevant data and prepares the environment map in advance, reducing the time required for subsequent motion calculations and improving overall processing speed.
Solution Approach 2:
The system continuously processes radar returns and updates the environment map in real-time, maintaining continuous motion determination without interruption. This continuous processing eliminates the latency associated with periodic or batch processing approaches.
3Device complexity
If radar data alone is used for localization, then device complexity is reduced, but measurement precision worsens
Solution Approach 1:
The patent makes the radar sensor multi-functional by enabling it to perform both environmental mapping and motion determination simultaneously. The same radar data is processed to create the environment map and to determine sensor platform motion, eliminating the need for separate sensors while maintaining comprehensive functionality.
Solution Approach 2:
The patent introduces an intermediary processing layer that transforms raw radar returns into both environment map data and motion parameters. This intermediary processing enables a single radar sensor to serve multiple purposes, achieving the functionality of multiple sensors through sophisticated data processing.
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
Improves localization and mapping accuracy, precision, and reliability by leveraging radar data for point cloud and pose data, while enhancing performance through advanced AI techniques, reducing the need for multiple sensors and improving interference mitigation, resolution, and latency.
Implementation Method 1
receiving a set of reflected probe signals from a plurality of stationary objects in an environment surrounding the radar sensor
Implementation Method 2
use radar Doppler information from stationary objects in an environment surrounding a radar sensor to determine only the velocity of the radar sensor
Data Source
AI summary
A method for radar-based localization and/or mapping, preferably including receiving sensor data, determining egospeed, and/or determining egorotation. The method can optionally include performing simultaneous localization and mapping. A system for radar-based localization and/or mapping, preferably including one or more radar sensors, and optionally including one or more vehicles and/or auxiliary sensors (e.g., coupled to the radar sensors).