Geometric detection based on one-dimensional laser range profiles of dynamic conical target

Area of Science:

• Electromagnetics and Optics
• Computational Physics
• Target Recognition

Background:

• One-dimensional laser range profiles (LRPs) provide rich data on object characteristics.
• Dynamic changes in target size and attitude significantly impact LRP peak projections.
• Accurate target characterization is crucial for various remote sensing and defense applications.

Purpose of the Study:

• To develop an efficient method for inverting the size and attitude of dynamic conical targets from LRPs.
• To validate the proposed inversion technique using simulated data of cones with varying parameters.
• To demonstrate the applicability of the inversion method to targets of arbitrary properties.

Main Methods:

• Establishment of ground, target, and incident field coordinate systems for LRP computation.
• Utilization of a genetic algorithm for the inversion of cone height and half-cone angle.
• Application of inversion results to determine target attitude angles over time.

Main Results:

• Successfully inverted the cone heights and half-cone angles for three distinct dynamic cones.
• Verified the accuracy of the theoretical model by successfully inverting attitude angles at various sampling times.
• Demonstrated the efficiency of the inversion technique for dynamic conical targets.

Conclusions:

• The proposed method effectively inverts size and attitude parameters of dynamic cones from LRP data.
• The genetic algorithm approach offers an efficient solution for target parameter estimation.
• The inversion technique shows potential for broad application to diverse targets in real-world scenarios.