In a scenario where GNSS signal is blocked due to interference or occlusion, it is of considerable value to establish a regional navigation system providing emergency services for ground users by using long-endurance and long-range fixed-wing Unmanned Aerial Vehicles (UAVs). The main work of this paper consists of two parts. First, we designed a set of UAV-based pseudolite navigation system (UAV-PNS) architecture based on fixed-wing UAVs. Then, considering the flight cost of the UAV swarm, the optimization of the UAV swarm’s flight path aimed at improving regional navigation performance was studied. In this paper, the fitness functions for UAVs’ flight path optimization are proposed, taking into account the navigation and positioning performance, the aircraft utilization rate of UAVs under flight constraints, and the response speed of the system to the emergency mission. Based on this, an acceptance–rejection mutated non-dominated sorting genetic algorithm III (ARMNSGA-III) is proposed for the UAVs’ flight path optimization. The research results show that the flight path strongly guarantees navigation service performance with constraints on the operating cost. The ARMNSGA-III proposed in this paper can provide a 44.01% algorithm timeliness improvement compared to the NSGA-III in the flight path optimization, supporting rapid establishment and continuous service of the UAV-PNS in emergency scenarios.

To enable autonomous route planning for UAV swarms in dynamic air–terrestrial cooperative navigation scenarios within GNSS-denied environments, this paper proposes a lightweight framework based on the Artificial Potential Field (APF) method. In the considered architecture, UAVs act as mobile transit navigation nodes that relay positioning information from sparse ground anchors to terrestrial users. For TOA-based cooperative positioning, the instantaneous geometric configuration of the UAV swarm significantly affects the overall system accuracy. Therefore, the impact of UAV positions on the end-to-end navigation performance is rigorously analyzed, yielding a comprehensive Dilution of Precision (DOP) matrix for the entire air–terrestrial system. By applying the Schur complement, the global performance metric is decomposed, resulting in a scalar evaluation function that directly reflects the geometric quality of the configuration. In practical scenarios involving dynamic and heterogeneous users, real-time trajectory adaptation of the UAV swarm is essential to continuously optimize user positioning accuracy. To this end, an APF-based autonomous joint route planning approach is developed. The potential field is constructed directly from the derived geometric evaluation model, where its negative gradient generates virtual forces that autonomously guide the UAV swarm. This elegantly bridges high-level navigation performance optimization with low-level motion control of the swarm. The simulation results show a 76.1% improvement in the average comprehensive GDOP for users compared to the baseline of hovering UAVs, validating the effectiveness and real-time capability of the proposed lightweight framework.

This paper proposes a GNSS-compatible method for characterizing the motion of UAV-based navigation enhancement platforms, designed to provide reliable navigation and positioning services in emergency scenarios where GNSS signals are unavailable or severely degraded. The method maps UAV trajectories into standard GNSS navigation messages by establishing a correspondence between ephemeris parameters and platform positions through coordinate transformation and Taylor series expansion. To address modeling inaccuracies, the approach incorporates truncation error analysis and motion-assumption compensation via parameter optimization. This design enables UAV-mounted pseudolite systems to broadcast GNSS-compatible signals without modifying existing receivers, significantly enhancing rapid deployment capabilities in complex or degraded environments. Simulation results confirm precise positional representation in static scenarios and robust error control under dynamic motion through higher-order modeling and optimized broadcast strategies. UAV flight tests demonstrated a theoretical maximum error of 0.4262 m and an actual maximum error of 3.1878 m under real-world disturbances, which is within operational limits. Additional experiments confirmed successful message parsing with standard GNSS receivers. The proposed method offers a lightweight, interoperable solution for integrating UAV platforms into GNSS-enhanced positioning systems, supporting timely and accurate navigation services in emergency and disaster relief operations.

To overcome the limitations of ground-based pseudolite systems susceptible to terrain obstructions, this article proposes an air–ground collaborative regional radio positioning system (AGCRRPS) in global navigation satellite system (GNSS)-denied environments, including architecture, evaluation metrics, and a systematic uncrewed aerial vehicle (UAV) swarm trajectory optimization method. The AGCRRPS operates through sequential pseudorange broadcasting and positioning among ground anchors, aerial UAV swarms, and ground users to ensure the stable operation of the system. The UAV swarm’s trajectory design directly impacts the propagation of system accuracy. To characterize the error propagation in this layered air–ground structure, we derive a precision mapping model suitable for multilayer systems and the equivalent dilution of precision (DOP) metric for instantaneous geometric configurations. Based on this, we formulate a multiobjective optimization function that effectively evaluates regional positioning systems, incorporating three dimensions: average accuracy, interuser balance, and temporal stability. An adaptive trajectory representation protocol that optimizes UAV trajectories while preserving primary task objectives is developed. By leveraging the nondominated sorting genetic algorithm II (NSGA-II) as the multiobjective optimizer, we establish a systematic UAV swarm trajectory optimization approach, with simulation results demonstrating its effectiveness. Further simulations reveal the precision limits and interlayer independence in multilayer systems, providing theoretical insights for weak-anchor multitier navigation system design. Additionally, the influence of resource allocation on user performance is analyzed, offering practical guidance for anchor–UAV ratio configurations in engineering deployments.