Optical Spread Spectrum Detection Resolving Multipath Signal Errors
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Solution Overview
Problem
Existing optical obstacle detection systems for unmanned vehicles face issues with false positives due to ambient noise and multipath propagation, and false negatives due to sensitivity issues, leading to inaccurate obstacle detection.
Innovation Solution
The system employs a light emitter and a line-image sensor, with a controller that determines whether a reflected light signal is a multi-path signal based on the time of flight and position along the sensor, and uses a control system coupled with an inertial measurement unit to control the vehicle and avoid detected objects, while also emitting light signals in patterns and using a shutter to filter out noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time of flight measurement is used for obstacle detection, then distance measurement capability is improved, but false positives occur due to ambient noise, multipath propagation, and phase jitter
Solution Approach 1:
The system segments the detection process by using a line-image sensor that divides the detection field into multiple spatial positions along the sensor array. Each position independently measures time of flight, allowing the system to distinguish multipath signals (which arrive at different positions) from direct path signals (which arrive at corresponding positions), thereby reducing false positives while maintaining distance measurement precision
Solution Approach 2:
The patent introduces an intermediary processing layer that correlates measurements across multiple sensor positions and uses spatial-temporal analysis to filter out multipath propagation effects. This intermediary processing distinguishes valid direct-path reflections from false multipath signals before final obstacle detection, improving reliability without sacrificing measurement precision
2Reliability
If light sensor sensitivity is increased to detect weak signals, then detection capability is improved, but false negatives occur due to swamping, flooding, or blooming issues
Solution Approach 1:
The line-image sensor divides the detection task across multiple spatially-separated photodetector elements. This segmentation prevents blooming and flooding effects that would occur in a single high-sensitivity sensor, as each element operates within its own dynamic range. The system maintains high detection capability while avoiding false negatives through this distributed sensing approach
Solution Approach 2:
The system uses multiple sensor positions (excessive spatial sampling) to detect the same optical signal from different angles. This partial redundancy allows the system to maintain detection capability even when individual sensor elements experience saturation or blooming, as other positions can still detect the signal without false negatives
3Measurement precision
If ambient noise filtering is applied to reduce false positives, then signal accuracy is improved, but detection time increases due to multiple verification steps
Solution Approach 1:
The system performs preliminary spatial filtering by comparing signal patterns across multiple sensor positions before final detection. By pre-identifying and eliminating multipath signals through spatial correlation analysis, the system reduces the need for multiple verification steps, thereby maintaining signal accuracy while minimizing additional detection time
Solution Approach 2:
The distributed line-image sensor array performs self-verification through inherent spatial redundancy. Each sensor position independently measures the signal, and the system automatically identifies consistent direct-path signals versus inconsistent multipath signals through spatial-temporal correlation, eliminating the need for external verification mechanisms and reducing detection time while maintaining accuracy
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 reduces false positives and negatives by accurately distinguishing between valid and multipath signals, enhancing the reliability of obstacle detection and vehicle control.
Implementation Method 1
a light emitter configured to emit a light signal
Implementation Method 2
a line-image sensor configured to receive reflected light signals at a plurality of positions along the line-image sensor
Data Source
AI summary
Example implementations may relate to an obstacle detection system. In particular, an example device may include a light emitter, a line-image sensor, and a controller that are mounted on a rotatable component. In an example embodiment, the line-image sensor may receive light signals emitted from the light emitter. The controller may be communicatively coupled to the light emitter and line-image sensor and configured to determine a multipath signal based on the time of flight of the light signal and the position along the line-image sensor at which the line-image sensor received the given reflected light signal.