Monopulse Calibration Table Using Radar Targets of Opportunity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing radar calibration methods rely on a single, specially identified target (PARROT) for generating calibration tables, which can be inaccurate due to errors in target or antenna positioning, and are limited to a single elevation angle, leading to incomplete and inaccurate data across all elevation angles.
Innovation Solution
A method using real-time data from multiple radar targets of opportunity to create a monopulse calibration table by normalizing signals from SUM and DIFF channels, calculating the center angle, determining off-boresight angles, and storing these in a table, with a running average and polynomial fitting to improve accuracy and account for elevation distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single specially identified target (PARROT) is used for calibration, then the calibration process is simplified, but the accuracy and completeness of the calibration table deteriorates due to positioning errors and single-elevation limitation
Solution Approach 1:
The calibration system is designed to accept and process data from multiple different targets at multiple different elevation angles, making the calibration process universally applicable across the entire radar operating envelope rather than being limited to a single target and elevation angle
Solution Approach 2:
The calibration process segments the data collection by gathering measurements from multiple discrete targets at different elevation angles, then combines these segmented datasets to form a complete and accurate calibration table that covers all operating conditions
2Measurement precision
If calibration data is collected from multiple targets at multiple elevation angles, then the calibration table accuracy and completeness improves, but the data processing complexity and computational requirements increase
Solution Approach 1:
The system automatically processes the multi-target calibration data through computer-implemented algorithms that perform normalization, correlation, and table generation without requiring manual intervention, allowing the complex processing to occur autonomously
Solution Approach 2:
Manual calibration procedures are replaced with automated computer-based processing that uses algorithms to normalize signals, calculate correlations, and generate the calibration table, substituting mechanical/manual operations with electronic/computational processes
3Productivity
If traditional monopulse calibration methods are used, then the azimuth measurement can be obtained, but the target positioning accuracy deteriorates due to beam width effects and uncorrected antenna pattern variations
Solution Approach 1:
The calibration table serves as a feedback mechanism that provides correction factors based on pre-measured antenna patterns at multiple elevation angles, allowing the system to compensate for antenna pattern variations and improve azimuth measurement accuracy
Solution Approach 2:
The system changes the calibration approach by collecting data across multiple elevation angles and using normalized signal correlations to create a comprehensive calibration table that accounts for antenna pattern variations across different operating conditions
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 generates a more accurate and comprehensive calibration table that improves target positioning accuracy across all elevation angles, even in dense environments, by using data from multiple targets and accounting for antenna elevation distortions.
Implementation Method 1
In a radar system, the azimuth location of an object in space can be determined in part by where a radio signal from the target originates from, relative to where the antenna is pointing
Implementation Method 2
The beamside direction is measured from the phase difference between the SUM and the DIFF channel. This phase is changed by 180 degrees from one side of the antenna boresight to the other
Data Source
AI summary
In a radar system, a monopulse calibration table is constructed from live targets of opportunity. A center of gravity or weighted average of normalized signals ΔV received at SUM and DIFF channels from a live target are used to determine the target's actual azimuth. Off bore sight angles (OBA) of the target are then determined from the target's actual azimuth. Normalized received signal values of ΔV are converted to nearest-valued integers. The OBA s that correspond to each integer-valued normalized received signal are averaged and can then be plotted as a function of normalized received signal value ΔV. Different tables or plots can be constructed for elevation angles. An equation of a best-fit line the matches or at least closely approximates the plotted data is determined to smooth the actual data.