Information-Optimal Formation Geometry Design for Multimodal UAV Cooperative Perception

The cooperative perception performance of unmanned aerial vehicle (UAV) swarms is governed by three-dimensional (3D) formation geometry, which dictates target observability, sensor complementarity, and communication quality. Despite this, existing literature largely treats formation geometry as a secondary byproduct of trajectory planning, neglecting its impact on multimodal sensing scenarios where heterogeneous payloads must be spatially arranged to exploit complementary perception strengths under communication interference and hardware budget constraints. To bridge this gap, this paper proposes an information-optimal framework that jointly optimizes UAV-sensor allocation, formation configuration, and flight control for multimodal cooperative perception. Specifically, a submodular greedy strategy grounded in Fisher Information Matrix (FIM) determinant maximization determines the optimal number of UAV-sensor allocation. Building upon this allocation, an equivalent formation transition strategy reconfigures UAV positions to enhance field-of-view (FOV) coverage and suppress inter-UAV communication interference. Furthermore, a Lyapunov-stable distributed flight controller leveraging logarithmic potential fields generates energy-efficient trajectories. Extensive simulations demonstrate that our formation-aware design achieves 25.0% improvement in FOV coverage, 104.2% enhancement in communication signal strength, and 84.7% reduction in control effort compared to conventional benchmarks.