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Cooperative Integrated Estimation-Guidance for Simultaneous Interception of Moving Targets

Lohitvel Gopikannan, Shashi Ranjan Kumar, Abhinav Sinha

TL;DR

The paper tackles the problem of simultaneous interception of a non-maneuvering target by a team of unmanned vehicles with heterogeneous sensing capabilities. It proposes a unified framework that fuses a prescribed-time distributed observer for target-state estimation with a true proportional navigation guidance law, achieving consensus on time-to-go within prescribed times $T_o$ and $T_a$ under directed communication. The main contributions include a novel prescribed-time observer over a directed sensing graph, a distributed time-to-go consensus protocol using the actuation graph Laplacian $\mathcal{L}_P$, and a robust guidance law that ensures cooperative interception even with sensorless agents and potential single-vehicle failures. The approach reduces sensing requirements, enhances scalability, and applies across aerial, terrestrial, and maritime domains, as demonstrated by simulations across constant-velocity and stationary-target scenarios. Overall, the framework offers a practical, provably stable method for coordinated interception with heterogeneous sensing in time-critical operations.

Abstract

This paper proposes a cooperative integrated estimation-guidance framework for simultaneous interception of a non-maneuvering target using a team of unmanned autonomous vehicles, assuming only a subset of vehicles are equipped with dedicated sensors to measure the target's states. Unlike earlier approaches that focus solely on either estimation or guidance design, the proposed framework unifies both within a cooperative architecture. To circumvent the limitation posed by heterogeneity in target observability, sensorless vehicles estimate the target's state by leveraging information exchanged with neighboring agents over a directed communication topology through a prescribed-time observer. The proposed approach employs true proportional navigation guidance (TPNG), which uses an exact time-to-go formulation and is applicable across a wide spectrum of target motions. Furthermore, prescribed-time observer and controller are employed to achieve convergence to true target's state and consensus in time-to-go within set predefined times, respectively. Simulations demonstrate the effectiveness of the proposed framework under various engagement scenarios.

Cooperative Integrated Estimation-Guidance for Simultaneous Interception of Moving Targets

TL;DR

The paper tackles the problem of simultaneous interception of a non-maneuvering target by a team of unmanned vehicles with heterogeneous sensing capabilities. It proposes a unified framework that fuses a prescribed-time distributed observer for target-state estimation with a true proportional navigation guidance law, achieving consensus on time-to-go within prescribed times and under directed communication. The main contributions include a novel prescribed-time observer over a directed sensing graph, a distributed time-to-go consensus protocol using the actuation graph Laplacian , and a robust guidance law that ensures cooperative interception even with sensorless agents and potential single-vehicle failures. The approach reduces sensing requirements, enhances scalability, and applies across aerial, terrestrial, and maritime domains, as demonstrated by simulations across constant-velocity and stationary-target scenarios. Overall, the framework offers a practical, provably stable method for coordinated interception with heterogeneous sensing in time-critical operations.

Abstract

This paper proposes a cooperative integrated estimation-guidance framework for simultaneous interception of a non-maneuvering target using a team of unmanned autonomous vehicles, assuming only a subset of vehicles are equipped with dedicated sensors to measure the target's states. Unlike earlier approaches that focus solely on either estimation or guidance design, the proposed framework unifies both within a cooperative architecture. To circumvent the limitation posed by heterogeneity in target observability, sensorless vehicles estimate the target's state by leveraging information exchanged with neighboring agents over a directed communication topology through a prescribed-time observer. The proposed approach employs true proportional navigation guidance (TPNG), which uses an exact time-to-go formulation and is applicable across a wide spectrum of target motions. Furthermore, prescribed-time observer and controller are employed to achieve convergence to true target's state and consensus in time-to-go within set predefined times, respectively. Simulations demonstrate the effectiveness of the proposed framework under various engagement scenarios.

Paper Structure

This paper contains 5 sections, 7 theorems, 46 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Background and Problem Formulation
  3. Design of the Proposed Framework
  4. Performance Evaluation
  5. Conclusions

Key Result

Lemma 1

For the $i^\text{th}$ pursuer, the dynamics of time-to-go eq:tgo has a relative degree of one with respect to its acceleration.

Figures (5)

  • Figure 1: Multiple pursuers engaging a single target
  • Figure 2: Pursuers' communication topologies.
  • Figure 3: Performance evaluation of the proposed strategy for a constant velocity target.
  • Figure 4: Performance evaluation of the proposed strategy when pursuer 3 fails.
  • Figure 5: Performance evaluation of the proposed strategy for a stationary target.

Theorems & Definitions (13)

  • Lemma 1
  • proof
  • Remark 1
  • Lemma 2
  • Lemma 3: sp3
  • Remark 2
  • Lemma 4: sp4
  • Lemma 5: sp3
  • Theorem 1
  • proof
  • ...and 3 more