Dual Kalman Filter for Passive Ranging Guidance
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Solution Overview
Problem
Current passive ranging systems for guiding interceptors lack accuracy in determining time-to-go during the terminal phase of flight, particularly when targets become closer and irradiance measurements become less reliable, leading to reduced guidance accuracy.
Innovation Solution
A dual Kalman Filter architecture is employed, with a first Kalman Filter processing target irradiance measurements before the target becomes resolved and a second Kalman Filter processing target area and length measurements after resolution, to improve time-to-go estimation and guidance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single Kalman Filter uses irradiance measurements for passive ranging, then the system can operate at long ranges, but the measurement precision deteriorates when the target becomes resolved and irradiance measurements become unreliable
Solution Approach 1:
The system divides the passive ranging process into two distinct segments: a first Kalman Filter that processes irradiance measurements when the target is unresolved (long range), and a second Kalman Filter that processes area and length measurements when the target is resolved (endgame phase). This segmentation allows each filter to use the most reliable measurement type for its specific operational phase, resolving the contradiction between long-range operation and measurement reliability.
Solution Approach 2:
The system changes the measurement parameters used by the Kalman Filter based on target range and resolution status. At long ranges, irradiance measurements are used; at endgame when the target is resolved, the system transitions to using area and length measurements. This dynamic parameter change ensures optimal measurement precision throughout the entire engagement phase.
2Measurement precision
If the system transitions from irradiance-based to area-based measurements, then the measurement precision improves during endgame, but the device complexity increases due to dual filter architecture
Solution Approach 1:
The guidance system is segmented into two functional modules (first and second Kalman Filters), each optimized for specific phases of the engagement. While this increases architectural complexity, it enables superior measurement precision by using the appropriate measurement type (irradiance or area/length) for each phase, ultimately improving overall guidance accuracy.
Solution Approach 2:
The system dynamically switches between two Kalman Filter configurations based on target range and resolution status. The first filter handles long-range irradiance measurements, while the second filter takes over for endgame area and length measurements. This dynamic adaptation optimizes guidance accuracy throughout the engagement while managing complexity through conditional operation.
3Ease of operation
If passive ranging is performed without own-ship maneuvers, then the ease of operation is improved, but the measurement precision of bearing-only estimation is insufficient for accurate time-to-go determination
Solution Approach 1:
The system changes the measurement parameters from bearing-only estimation to include irradiance, area, and length measurements. By incorporating these additional parameters into the Kalman Filter, the system achieves accurate time-to-go determination without requiring own-ship maneuvers, maintaining ease of operation while improving measurement precision.
Data Source
AI summary
A target intercept system for guiding an interceptor to a target using passive ranging includes an EO/IR sensor that provides target azimuth and elevation angles, target irradiance, target area and target length. A dual Kalman Filter architecture is implemented where, prior to a target image becoming resolved, i.e., prior to endgame, a first Kalman Filter provides guidance as a function of target azimuth and elevation angles and target irradiance measurements. After the target image becomes resolved, i.e., at endgame, a second Kalman Filter provides guidance as a function of target azimuth and elevation angles, target area and, optionally, target length, instead. The dual Kalman Filter approach improves the estimates of time-to-go by optimizing the on-board EO/IR sensor measurements at the optimal times.