Adaptive Nonlinear Trajectory Shaping for Multi-Mode Guidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional guidance subsystems face limitations in adapting to uncertainties such as target location and maneuvering errors, sensor noise, and nonlinear shaping capabilities, making them inadequate for multi-mission and multi-mode operations.
Innovation Solution
A nonlinear trajectory shaping guidance law with adaptive gain calculations for velocity and position, incorporating high-order shaping coefficients, lift/drag information, and data from target and projectile state estimators, which accounts for seeker look angle constraints and enables real-time predicted intercept point calculations to optimize impact angles and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional guidance laws (PN, CLOS, basic NTS) are used, then the system structure is simple, but the adaptability to multi-mission and multi-mode operations is insufficient
Solution Approach 1:
The guidance law is designed with a unified mathematical framework that can handle multiple mission types (surface-to-surface, air-to-surface, air defense) and multiple engagement modes through adaptive gain scheduling and parameter adjustment, eliminating the need for separate guidance laws for different scenarios
Solution Approach 2:
The guidance law employs time-varying adaptive gains K1(t) and K2(t) that dynamically adjust during flight based on remaining time-to-go and mission phase, allowing the same guidance system to adapt its behavior for different mission requirements without structural changes
2Reliability
If conventional guidance laws are used, then the computational requirements are low, but the capability to handle target maneuvering and location errors is limited
Solution Approach 1:
The guidance law continuously uses feedback from target state estimators and projectile state estimators to update the predicted intercept point and adjust guidance commands in real-time, compensating for target maneuvers and measurement errors through closed-loop control
Solution Approach 2:
The guidance law performs preliminary calculation of the predicted intercept point (PIP) using estimated target future position and velocity, allowing the system to proactively adjust for anticipated target maneuvers rather than reacting after errors occur
3Manufacturing precision
If basic NTS guidance is used, then the implementation is straightforward, but the impact angle control precision is insufficient
Solution Approach 1:
The guidance law uses high-order shaping coefficients (beyond the basic NTS coefficients) to precisely control the trajectory curvature and shape, enabling accurate impact angle enforcement through refined parameter adjustment in the acceleration command calculation
4Productivity
If adaptive gain calculations are implemented, then the performance against uncertainties improves, but the computational load increases
Solution Approach 1:
The guidance law implements adaptive gains selectively based on mission phase and uncertainty levels, using full adaptive calculation only when needed (e.g., during terminal phase or high-uncertainty conditions) rather than continuously, optimizing the balance between performance and computational energy cost
Data Source
AI summary
A method and system for nonlinear trajectory shaping guidance law capable of providing a robust guidance solution suitable for multi-mission, multi-mode operations. The nonlinear trajectory shaping guidance law offers (1) a dual layered GL gains calculation: (i) NTS time varying adjustment accounting for engine on/off and L/D variation and (ii) general explicit guidance algorithm based sub-optimal fixed-gain selection while still maintaining its trajectory shaping capability for short range to go missions; (2) flight path angle (FPA) command tracking and following to ensure a high probability of target destruction while minimizing collateral damages; (3) high precision impact point calculation factoring in target location errors or motion and maneuvering uncertainties; and (4) heading error angle minimization.