Aiming at the problem of Unmanned Aerial Vehicle (UAV) swarm fragmentation caused by the velocity disorder in the process of spoofing, this paper designs a distributed UAV swarm countermeasure method based on Global Navigation Satellite System (GNSS) spoofing, which realizes the purpose of spoofing and controlling illegal small UAV swarm. In this paper, the dynamic model of distributed UAV swarm is first constructed, the coupling relationship between GNSS spoofing offset and the navigation state parameters of UAV swarm is derived. Then, the slope of slop-type position spoofing signal is used to represent the velocity spoofing offset, and the velocity of swarm is controlled by controlling the slope of slop-type position spoofing signal. Based on the consistency control principle of swarm, the location of whole swarm is driven by spoofing the positioning information of individual, so as to realize the spoofing of the whole target UAV swarm. Finally, it is proved that using this method to spoof the individual of UAV swarm can achieve countermeasures against the whole UAV swarm under the premise of ensuring the integrity and velocity order of swarm through simulation and semi-physical experiments.

In order to solve the spoofing problem of SINS/GNSS tightly integrated navigation system with inertial assist spoofing detection module, this paper proposes a covert spoofing algorithm for SINS/GNSS tightly integrated navigation system. Firstly, the influence mechanism of the GNSS spoofing signal on the innovation and state estimation parameters of the SINS/GNSS tightly integrated navigation system is analyzed, and then the GNSS spoofing signal model is established with the constraint condition of the influence of the GNSS spoofing signal on the innovation and state estimation parameters of the SINS/GNSS tightly integrated navigation system. Secondly, the mathematical model of covert spoofing is constructed by using the GNSS spoofing signal model. Finally, SINS/GNSS tightly integrated navigation system is spoofed by GNSS spoofing signal generated according to the mathematical model of covert spoofing. Note to Practitioners—The motivation of this paper is to solve the spoofing problem of SINS/GNSS tightly integrated navigation system, so as to realize the control of the illegal unmanned platform equipped with tightly integrated navigation system. The existing spoofing methods are easily detected by the spoofing detection module, and it is difficult to meet the spoofing requirements of SINS/GNSS tightly integrated navigation system equipped with inertial aided spoofing detection module. This paper proposes a covert spoofing algorithm. Firstly, the influence mechanism of GNSS spoofing signal on SINS/GNSS tightly integrated navigation system is analyzed. Then, the mathematical model of covert spoofing is established by taking the influence of GNSS spoofing signal on the innovation parameter and state estimation parameters of SINS/GNSS tightly integrated navigation system as the constraint condition. Finally, the GNSS spoofing signal generated by the covert spoofing mathematical model is used to spoof the SINS/GNSS tightly integrated navigation system. Simulation and experimental results verify the effectiveness and correctness of the proposed method. In the future research, we will further promote the experiment and application of spoofing technology in the control of various illegal unmanned platforms.

To realize the defense task of precise directional drive off of unmanned combat system in the target area, an anti-unmanned directional drive-off method under SINS(Strapdown Inertial Navigation System)/GPS(Global Positioning System) integrated navigation mode is proposed in this paper, which is suitable for the security defense of important places, urban public security protection and anti-terrorism and stability maintenance in sensitive areas. Firstly, this paper constructs a seven dimensional SINS/GPS integrated navigation model of unmanned combat system including horizontal position, velocity and attitude, and uses discrete Kalman filter for data fusion; Then, combined with the coupling relationship between various state parameters of SINS/GPS integrated navigation, the controllability and stability of false satellite signal acting on the position output of integrated navigation are analyzed, and then the feasibility of satellite navigation spoofing under SINS/GPS integrated navigation mode is deduced; Finally, the false satellite signal is designed and constructed to make the position estimation of SINS/GPS Integrated Navigation drive away accurately. The simulation and experimental results verify the effectiveness and correctness of the anti-unmanned directional drive-off method under the integrated navigation mode.Note to Practitioners—This work is motivated by the need for the defense task of precise directional drive off of unmanned combat system in the target area. Most unmanned combat platforms adopt the integrated navigation mode with satellite navigation system as an auxiliary means. It can be challenging for researchers and practitioners to drive off the unmanned combat system which adopt the integrated navigation mode in the target area by the existing spoofing methods. Therefore, this paper presents an accurate directional displacement method against unmanned under the SINS/GPS integrated navigation mode and the effectiveness of the proposed method is verified by UAV spoofing simulation and test. This paper provides researchers and practitioners with comprehensive reference sources in anti-Unmanned directional drive-off method under integrated navigation mode, which can help them develop suitable solutions to drive off the unmanned combat system which adopt the integrated navigation mode in the target area.

To address the critical issue of public safety threats caused by disordered low-altitude UAV operations, this paper proposes DG-MFCO (Dual-stage Greedy-Driven & Multi-step Foresight Collaborative Optimization), a deceptive source deployment optimization scheme. The algorithm aims to achieve maximum interference coverage with minimal deceptive sources, thereby effectively intercepting unauthorized UAVs. The methodology initiates with a three-dimensional airspace modeling process: the target area undergoes grid discretization followed by vertical stratified sampling to generate elevation-embedded spatial point clouds. We establish a terrain-aware interference station deployment model by integrating ray tracing principles and viewshed analysis, complemented by defining a comprehensive 3D interference coverage evaluation criterion. The solution adopts a dual-stage optimization strategy. In the preliminary phase, a parallelized greedy algorithm rapidly identifies optimal positions with maximal coverage contribution. The advanced phase implements a multi-step neighborhood foresight mechanism, employing a distance-decay weighted function to assess potential values of uncovered regions, ultimately selecting positions with maximum potential as optimal deceptive source locations. The final results indicate that under complex mountainous terrain conditions, compared to the greedy algorithm and the particle swarm optimization algorithm, the DG-MFCO algorithm achieves a stable 90% full airspace coverage ratio by deploying only eight deceptive sources, while demonstrating strong robustness and repeatability. This proves the engineering practicality of the proposed method in complex topographic conditions.

In strapdown vehicle gravimetry, a new phenomenon was discovered by strapdown vehicle gravimetry error model analysis and simulation. That is, after compensating all error terms in the gravity measurement error model, there is still residual error in gravity results, which could not be described by the model. In response to this, multiscenario simulations were carried out to study the characteristics of this residual nonmodel error. Simulations manifest that the nonmodel error has close relationship with the navigation data recorded during strapdown vehicle gravity measurement. On the basis of this, this letter proposed a strapdown vehicle gravimetry nonmodel error compensation method. This method could estimate the nonmodel error by strapdown vehicle gravimetry simulation, employing the real integrated navigation data and the strapdown inertial navigation system (SINS) real trajectory generator. The effectiveness of the proposed method was verified by a real strapdown vehicle gravimetry test in Changsha. Test results show that the repeatability of the repeat lines under 200 s filtering has been improved from 0.51 to 0.41 mGal, 19.6% increase in accuracy. It demonstrates that the proposed method is correctness and validity in real strapdown vehicle gravimetry application.

In view of the fact that there are dynamic errors in the strapdown dynamic gravimetry, based on the analysis of the error mechanism of the strapdown dynamic gravimetry, a general model to compensate the dynamic error of the strapdown dynamic gravimetry is proposed, and the constraints are established by using the correlation analysis; then, the parameters of the model are estimated. The effectiveness of the proposed method is verified by using the strapdown airborne gravimetry data under the undulated flight conditions. The results show that the repeatability of the repeated gravity measurements under 160-s filtering is improved from 1.41 to 0.70 mGal, while the result under 300-s filtering is 0.62 mGal. It shows that this method can effectively eliminate the dynamic error while maintaining the spatial resolution.