Radar Sensor Fusion for Accurate Low-Power Interaction Detection
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Solution Overview
Problem
Conventional sensors in computing devices suffer from limited accuracy, range, and functionality, leading to incorrect user input and user frustration due to inaccurate sensing of device surroundings.
Innovation Solution
Implementing radar-enabled sensor fusion by combining radar data with data from other sensors to enhance accuracy and resolution, using radar features to activate supplemental sensors and configure contextual settings based on 3D context models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors are used to sense device surroundings, then the device can detect basic environmental changes, but the sensing accuracy and range are limited leading to incorrect user input detection
Solution Approach 1:
The patent combines radar sensing technology with conventional sensors (accelerometer, proximity sensor, touch screen) to create a sensor fusion system. The radar sensor provides high-accuracy detection of user presence and hand gestures, while conventional sensors detect basic device movement and proximity. By merging these different sensing modalities, the system achieves superior measurement precision without requiring a complete replacement of the existing sensor ecosystem.
Solution Approach 2:
The radar sensor serves multiple functions within the system: detecting user presence, tracking hand gestures, determining spatial relationships, and providing input for both proximity-based and gesture-based interactions. This multi-functionality allows a single radar component to replace or supplement multiple specialized sensors, improving accuracy while managing system complexity through consolidation.
2Measurement precision
If radar sensor is added to improve sensing accuracy, then user interaction detection precision increases, but device complexity and processing requirements increase
Solution Approach 1:
The patent introduces a sensor fusion engine as an intermediary component that processes and integrates data from the radar sensor and conventional sensors. This mediator translates raw radar data into meaningful gestures and interactions, coordinating the outputs of different sensor types and presenting unified interaction data to the operating system. This intermediary layer manages the complexity of sensor fusion while enabling high-precision user interaction detection.
Solution Approach 2:
The radar sensor replaces the need for complex mechanical or optical gesture recognition systems by using electromagnetic wave reflection to detect hand movements and gestures. This substitution achieves high-precision gesture detection without requiring cameras, depth sensors, or complex mechanical components, thereby improving accuracy while actually reducing overall system complexity.
3Reliability
If multiple sensors are activated continuously to ensure accurate detection, then sensing reliability improves, but energy consumption increases
Solution Approach 1:
The sensor fusion engine implements periodic activation of the radar sensor based on detected conditions. Instead of continuous operation, the radar sensor is activated periodically when the proximity sensor detects a user's presence or when specific conditions are met. This periodic action maintains detection reliability by ensuring the radar sensor is active when needed while significantly reducing energy consumption compared to continuous operation.
Solution Approach 2:
The system uses the proximity sensor as a trigger mechanism that automatically activates the more energy-intensive radar sensor only when a user is detected nearby. This self-service approach allows the low-power proximity sensor to manage the power consumption of the high-precision radar sensor, ensuring reliable detection only when necessary and minimizing overall energy consumption throughout device operation.
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 the performance of sensor-based applications by increasing accuracy and resolution, enabling precise user interaction and contextual awareness.
Implementation Method 1
a radar sensor is provided that emits electromagnetic waves and receives reflection signals from a target
Implementation Method 2
a radar sensor is provided that emits electromagnetic waves and receives reflection signals from a target
Data Source
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AI summary
This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.