Doppler Radar Flock Detection Using Radial Velocity Spectra
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Solution Overview
Problem
Conventional remote sensing systems struggle with accurately interpreting aggregations of remote sensor returns, particularly in identifying non-stationary objects like wildlife feeding flocks, and often require skilled operators to interpret complex data.
Innovation Solution
A remote sensing imagery system incorporating radar assemblies, colocated imaging modules, and logic devices to automatically detect and identify wildlife feeding flocks by analyzing radial velocity spectra and generating intuitive imagery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional remote sensing systems are used to detect wildlife feeding flocks, then the system can provide basic remote sensing data, but the accuracy of identifying non-stationary objects like feeding flocks is poor and requires skilled operators to interpret complex data
Solution Approach 1:
The system automatically detects and identifies wildlife feeding flocks using radar assemblies and logic devices that analyze radial velocity spectra, enabling the system to serve itself without requiring skilled human operators to interpret complex remote sensing data
Solution Approach 2:
The system transforms complex remote sensing data into intuitive imagery by changing the presentation parameters from raw sensor returns to processed visual displays that automatically highlight feeding flock characteristics through radial velocity spectrum analysis
2Reliability
If conventional remote sensing systems provide basic data, then the system complexity is low, but the reliability of detecting aggregations of remote sensor returns is poor
Solution Approach 1:
The system combines radar assemblies with colocated imaging modules and integrates multiple sensor returns into a unified detection system, merging separate functions to achieve reliable automatic identification of feeding flocks
Solution Approach 2:
The logic device acts as an intermediary between the radar assemblies and the final detection output, processing and analyzing radial velocity spectra to reliably identify feeding flocks without requiring direct human interpretation of raw data
3Loss of information
If the system processes aggregations of remote sensor returns, then comprehensive data is collected, but the difficulty of interpreting the data increases
Solution Approach 1:
The system replaces the mechanical process of human data interpretation with automated logic devices that use algorithms to analyze radial velocity spectra and generate intuitive imagery, eliminating the difficulty of manual data interpretation
Solution Approach 2:
The system creates a simplified copy or representation of the complex sensor data in the form of intuitive imagery that automatically highlights feeding flock characteristics, making the information accessible without requiring experts to interpret the original complex datasets
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
Provides highly accurate and accessible remote sensing imagery that intuitively identifies wildlife feeding flocks, reducing operator reliance and enhancing situational awareness for mobile structures.
Implementation Method 1
determine a radial velocity spectrum associated with the detected target based, at least in part, on the received radar returns
Data Source
AI summary
Techniques are disclosed for systems and methods to provide wildlife feeding flock detection using a remote sensing imagery system. A remote sensing imagery system includes a radar assembly mounted to a mobile structure and a coupled logic device. The logic device is configured to receive radar returns corresponding to a detected target, determine a radial velocity spectrum associated with the detected target based, at least in part, on the received radar returns, and determine a probability the detected target includes a feeding flock based, at least in part, on the determined radial velocity spectrum. The logic device may generate radar image data based on the received radar returns, the determined radial velocity spectrum, and/or the probability the detected target includes the feeding flock. Subsequent user input and/or the sensor data may be used to adjust a steering actuator, a propulsion system thrust, and/or other operational systems of the mobile structure.