Doppler Lidar Signal Processing Reliability Index Calculation
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Solution Overview
Problem
Conventional technologies fail to appropriately evaluate the reliability of observation signals in Doppler lidar systems, leading to erroneous signal recognition and performance degradation, especially in low signal-to-noise ratio conditions, which can result in inappropriate control surface adjustments for aircraft.
Innovation Solution
A signal processing device that intermittently integrates reception signals using multiple systems to generate multiple data sets, allowing for the calculation of a reliability index by comparing Doppler shift amounts, thereby evaluating signal reliability and distinguishing between correct and erroneous data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional Doppler lidar systems use reception signals directly for airflow measurement, then the system structure remains simple, but erroneous signals occur due to noise and low signal-to-noise ratio
Solution Approach 1:
The reception signal processing is segmented into multiple integration operations (first integration unit and second integration unit) that process signals differently. The first integration unit performs integration over a longer period while the second integration unit integrates over a shorter period, allowing comparison between multiple integrated results to identify and eliminate erroneous signals.
Solution Approach 2:
The system implements feedback by comparing the integrated results from multiple integration units and using this comparison to determine signal reliability. The reliability determination unit uses the comparison result to validate whether the reception signal is correct, creating a feedback loop that continuously monitors and validates signal quality.
2Reliability
If multiple integration systems are used to evaluate signal reliability, then signal reliability improves, but processing time increases
Solution Approach 1:
The system uses periodic integration operations with different time periods. The first integration unit integrates over a first time period while the second integration unit integrates over a second time period that is shorter than the first. This periodic multi-timescale integration allows reliability assessment without requiring continuous complex processing.
Solution Approach 2:
The integration operations are performed in advance before final signal validation. By pre-integrating signals through multiple pathways and storing these integrated results, the system prepares reliability assessment data beforehand, reducing the computational burden during real-time validation.
3Length of stationary object
If long-distance observation information is used alone to improve observation range, then observation distance increases, but signal-to-noise ratio decreases leading to erroneous detections
Solution Approach 1:
The system merges multiple integrated signal results from different integration units to assess overall signal quality. By combining the results from the first integration unit and second integration unit through comparison, the system can validate long-distance signals against multiple integration outcomes, reducing the impact of noise on distant observations.
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 effectively reduces the use of incorrect data by quantitatively determining signal reliability, improving the accuracy of wind velocity measurements and reducing the likelihood of using unreliable data for aircraft control surface adjustments.
Implementation Method 1
a first integration unit that intermittently integrates a signal train corresponding to a reception signal by using a plurality of systems to obtain a plurality of pieces of integrated data
Implementation Method 2
a reliability index calculation unit that calculates a reliability index of the reception signal by comparison based on the plurality of pieces of integrated data
Data Source
Figure 1
Figure 2
Figure 3~3(c)
AI summary
[Object] To appropriately evaluate reliability of a reception signal. [Solving Means] A signal processing unit 20 includes a first integration unit 21, a Doppler detection unit 22, and a comparator circuit 28 as a reliability index calculation unit. The first integration unit 21 intermittently integrates a pulse train corresponding to a reception signal by using two systems and obtains two pieces of integrated data. The Doppler detection unit 22 divides each of the two pieces of integrated data into a plurality of range bins in time series, obtains a relationship between a frequency and intensity in each range bin for each of the two pieces of integrated data, and detects a Doppler shift amount from the relationship. The comparator circuit 28 calculates a reliability index of the reception signal by comparing the Doppler shift amounts (wind velocity values) of the two pieces of integrated data.