No abstract

Jamming resources allocation ( JRA) is an essential task in clustered combat environments. Especially in cases with multiple threats, efficient JRA is imperative for protecting key assets. In this study, multiple distributed outboard jammers protecting multiple targets against a multi-missile threat are considered, where the function of JRA includes jamming object selection and jammer power allocation. To address this problem, first, a scheme to evaluate the jamming effectiveness of the radar seeker under cooperative jamming from multiple jammers is proposed. Considering power allocation, a mixed-integer programing model for the optimisation of JRA is further established. A two-track simultaneous update binary particle swarm algorithm (TS-BPSO) is then devised to obtain the solutions of the JRA. Finally, the effectiveness of the proposed method for multiple jammers in the multiple missiles scenario is evaluated through simulations. The simulation results suggest that the distributed cooperative jamming resource allocation is affected by the incoming orientation of the missile and the relative position of the jammers and the targets. The findings of the study enable evaluating the use of jammer formations and provide insights into developing effective jamming strategies. K E Y W O R D S distributed outboard jammers, jamming effectiveness assessment, jamming resources allocation, multi-missile threat, TS-BPSO This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.

No abstract

The existing off-board active decoys face such common technical problems as short action time, limited jamming power, and difficult control over deployment situation and effective directive jamming beam direction. For this reason, this paper introduces a new mode and process of anti-missile combat, which places the radar active decoy on an unmanned surface vehicle (USV) to collaborate with the surface warship during the off-board active anti-missile combat. Following the principles of radar terminal guidance centroid jamming, a real-time calculation method for the effective area of off-board active jamming is developed, and the jamming position maneuver strategy under the collaboration of the USV and the surface warship is proposed to implement the off-board active anti-missile combat. The proposed strategy satisfies the needs of long-time, high-power, stable, and effective off-board jamming against incoming anti-ship missiles. This paper further verifies the effectiveness of the proposed strategy in the simulated and live firing confrontations. INDEX TERMS electronic countermeasures unmanned surface vehicle (ECM USV); off-board active decoy; centroid jamming; jamming-position maneuver.

No abstract

An adaptive channel estimation algorithm for the channel length is proposed to construct a channel estimation model suitable for orthogonal frequency division multiplexing (OFDM) underwater acoustic communication signals for the dependence of traditional channel estimation algorithms on channel length information. This algorithm can be adopted to evaluate channel estimation quality in real time and to adaptively adjust the channel length of the channel estimation algorithm according to the evaluation result, which satisfies the need of accurate estimation of unknown underwater acoustic channels and communication application; based on the study on the relationship between the OFDM communication bit error rate and the subcarrier signal to noise ratio, a self-adjusting optimization scheme for OFDM subcarrier transmitting power is proposed, which realizes underwater communication with the low bit error rate through higher energy efficiency. The validity of the research content is verified through simulation and field experiments.

No abstract