Doppler Lidar Signal Filtering for Ground Reflection Removal
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Solution Overview
Problem
Existing Doppler Lidars face challenges in accurately distinguishing between airflow data and ground reflections during a landing approach, leading to erroneous detections due to the higher intensity of ground reflections compared to atmospheric aerosol particles, which affects the reliability of airflow observation.
Innovation Solution
A remote airflow observation device and method that utilizes a signal processor to distribute received signals into range bins, detect hard targets like the ground, and exclude signals derived from these targets by analyzing intensity changes, frequency fluctuations, and spectral characteristics, thereby improving the reliability of airflow observation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If ground reflections are included in the received signal, then the signal intensity is high, but the measurement precision of airflow observation deteriorates due to erroneous detections
Solution Approach 1:
The received signal is segmented into multiple range bins corresponding to different distance intervals. By dividing the signal processing into discrete range segments, the system can identify and exclude ground reflection signals in specific range bins while preserving atmospheric aerosol signals in other bins, thereby maintaining measurement precision while utilizing high-intensity signals where valid.
Solution Approach 2:
The signal processing unit extracts and removes ground reflection components from the received signal by identifying characteristic features such as high intensity values and specific range bin patterns. This extraction process separates the harmful ground reflection signals from the useful atmospheric aerosol signals, eliminating erroneous detections while preserving valid airflow data.
2Measurement precision
If ground reflections are detected and excluded, then the measurement precision improves, but the device complexity increases due to additional signal processing requirements
Solution Approach 1:
The system performs preliminary range bin distribution and ground reflection detection before final wind speed calculation. By preparing and identifying ground reflection signals in advance through range bin analysis, the system eliminates the need for complex post-processing corrections, reducing overall computational complexity while maintaining high measurement precision.
Solution Approach 2:
The signal processing unit uses the inherent characteristics of ground reflection signals (high intensity, specific range bin distribution) to automatically identify and exclude them without requiring external intervention or complex algorithms. The system serves itself by utilizing the distinctive features of the interference signals to detect and remove them, minimizing additional processing complexity.
3Productivity
If signal integration is performed over all range bins, then the productivity of observation is high, but the reliability deteriorates due to inclusion of erroneous ground reflection signals
Solution Approach 1:
The integration process is segmented to exclude specific range bins containing ground reflection signals while integrating signals from range bins containing atmospheric aerosols. This selective integration maintains high productivity by processing available signals efficiently while improving reliability by excluding erroneous ground reflection data from the integration calculation.
Solution Approach 2:
Different quality weights are applied to different range bins based on their content characteristics. Range bins containing atmospheric aerosol signals are included in integration with full weight, while range bins containing ground reflection signals are excluded or weighted differently. This local quality differentiation ensures reliable integration results while maintaining high observation productivity.
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
The solution effectively eliminates the influence of ground reflections, enhancing the accuracy and reliability of airflow observation by distinguishing between atmospheric and ground-derived signals, thus improving the overall performance of Doppler Lidars.
Implementation Method 1
The Doppler Lidar irradiates dust (aerosol) in the atmosphere with laser to extract Doppler shift components of scattered light thereof. This makes it possible to detect the speed of a target at each distance.
Implementation Method 2
The Doppler Lidar irradiates dust (aerosol) in the atmosphere with laser to extract Doppler shift components of scattered light thereof.
Data Source
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AI summary
[Object] To provide a remote airflow observation device, a remote airflow observation method, and a program that are capable of eliminating the influence of scattered waves from the ground or some object and improving the reliability of airflow observation. [Solving Means] A Doppler Lidar 100 includes: a measurement unit 110 that radiates transmission light including pulse-form laser light, receives reflected light of the radiated transmission light as reception light, and outputs a received signal for calculating a wind speed value on the basis of the transmission light and the reception light; and a signal processor 8 that performs processing for distributing the received signal to range bins by time-dividing the received signal and for removing a signal derived from a hard target from the received signal.