Optical Sensor Adaptive Kalman Filter for Moving Object Detection
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Solution Overview
Problem
Optical sensors face measurement errors and increased reaction time when detecting moving objects due to position or distance changes, leading to falsified results and lag errors, especially when averaging measured values.
Innovation Solution
The implementation of an adaptive Kalman filter that continuously adjusts filter coefficients to current changes in measured values, allowing for real-time filtering of individual measurements and reducing noise, enabling precise object detection even at high speeds without compromising measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If averaging methods are used to reduce measurement errors, then measurement accuracy is improved, but reaction time is increased and trailing errors occur when objects move relative to the sensor
Solution Approach 1:
The patent applies dynamic filtering by switching between different filter types (moving average filter and exponential moving average filter) based on the detected motion state of the object. When motion is detected, the system transitions to a filter that adapts to changing positions, preventing trailing errors while maintaining measurement accuracy. This dynamic adaptation resolves the contradiction by making the filtering process responsive to real-time conditions rather than using a static averaging method.
Solution Approach 2:
The patent changes the filtering parameters dynamically based on motion detection. The system monitors the measured values to detect motion and adjusts the filter coefficients accordingly - using a moving average filter for stationary objects and an exponential moving average filter for moving objects. This parameter change allows the system to maintain both high measurement accuracy and fast reaction time by selecting the appropriate filtering strength based on current conditions.
2Measurement precision
If averaging methods are used to reduce measurement errors, then measurement accuracy is improved, but trailing errors occur when the object's position changes during averaging
Solution Approach 1:
The system dynamically switches filtering strategies based on detected motion. When an object is detected to be moving, the patent applies an exponential moving average filter that gives more weight to recent measurements, preventing the trailing errors that occur with standard averaging. This dynamic approach maintains measurement validity by adapting the filtering method to the object's motion state.
Solution Approach 2:
The patent implements feedback by continuously monitoring the measured values to detect motion and adjusting the filter type accordingly. The system uses the measured position or distance values to determine whether to apply a moving average filter (for stationary objects) or an exponential moving average filter (for moving objects). This feedback mechanism ensures that the filtering process maintains measurement validity by responding to real-time changes in the object's position.
3Measurement precision
If filter coefficients are adjusted continuously to adapt to changing measured values, then measurement accuracy is improved for moving objects, but device complexity increases
Solution Approach 1:
The patent changes filtering parameters based on motion detection rather than continuously adjusting all filter coefficients. The system switches between two well-defined filter types (moving average and exponential moving average) based on a simple motion detection threshold. This discrete parameter change approach maintains high measurement accuracy for moving objects while avoiding the complexity of continuously adapting multiple filter parameters simultaneously.
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 improves measurement accuracy and reduces noise in optical sensors, allowing for precise detection of moving objects and faster reaction times by adapting to changing noise power ranges and movement scenarios, thereby enhancing the sensor's performance without increasing costs or structural size.
Implementation Method 1
the optical sensor comprises a transmit/receive unit with at least one transmitter emitting light beams and one receiver receiving light beams. For object detection, the transmitted light beams are typically directed towards the object, reflected by it, and then directed as received light beams to the receiver.
Data Source
Figure 1
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Figure 4a~4b
AI summary
The invention relates to an optical sensor (1) for detecting objects (12) with a transmit/receive unit (2), comprising a transmitter (3) emitting transmit light beams (8) and a receiver (4) receiving receive light beams (9), and with an evaluation unit (5) in which a temporal sequence of measured values is generated depending on received signals from the receiver (4), wherein the measured values are distance values or position values. At least one adaptive Kalman filter, in which the measured values are filtered, is provided.