Addressing the high-dimensional, strongly constrained multi-objective optimization problem of air–ground collaborative jamming scheduling in complex terrain, existing methods are often limited by incomplete modeling and low optimization efficiency in discrete feasible regions. This paper proposes a Terrain-Aware Multi-Scale Discrete Operator (TA-MSDO). A joint optimization model integrating discrete terrain characteristics and practical combat constraints is first constructed. Then, by leveraging the topological adjacency of terrain units, TA-MSDO employs a block-level crossover and a multi-scale mutation mechanism, replacing traditional continuous genetic operations to enable efficient and directional exploration of the discrete feasible region. Integrating TA-MSDO into the NSGA-III framework yields the enhanced ENSGA3 algorithm. Experimental results in a typical hilly terrain scenario demonstrate that ENSGA3 achieves a statistically significant performance improvement over the decomposition-based MOEA/D algorithm in terms of maximum achievable suppression effectiveness and hypervolume. As a comprehensive metric integrating convergence and Pareto frontier coverage, hypervolume further verifies the superior comprehensive optimization capability of the proposed algorithm. Meanwhile, compared with other classic mainstream multi-objective optimization algorithms including NSGA-II, standard NSGA-III and SPEA2, the proposed algorithm exhibits clear positive advantages in the upper bound of suppression effectiveness for elite solutions and operational stability across random initializations, with a favorable trend in Pareto frontier coverage for multi-objective collaborative optimization. This work provides an effective solution for jamming resource scheduling in complex battlefield environments.

Air–ground joint jamming enables three-dimensional, distributed jamming configurations, making it effective against air–ground communication networks with complex, dynamically adjustable links. Once the jamming layout is fixed, dynamic jamming power scheduling becomes essential to conserve energy and prolong jamming duration. However, existing methods suffer from poor applicability in such scenarios, primarily due to their sparse deployment and adversarial nature. To address this limitation, this paper develops a set of mathematical models and a dedicated algorithm for air–ground communication countermeasures. Specifically, we (1) randomly select communication nodes to determine the jammer operation sequence; (2) schedule the number of active jammers by sorting transmission path losses in ascending order; and (3) estimate jamming effects using electromagnetic wave propagation characteristics to adjust jamming power dynamically. This approach formally converts the original dynamic, stochastic jamming resource scheduling problem into a static, deterministic one via cognitive certainty of dynamic parameters and deterministic modeling of stochastic factors—enabling rapid adaptation to unknown, dynamic communication power strategies and resolving the coordination challenge in air–ground joint jamming. Experimental results demonstrate that the proposed Transmission Loss Ordering Algorithm (TLOA) extends the system operating duration by up to 41.6% compared to benchmark methods (e.g., genetic algorithm).

In extreme scenarios, to prevent the leakage of jamming coordination information, the jammers must proactively terminate their communication functions and implement jamming resource scheduling via Non-Networked Cooperation. However, current research on this non-networked jamming approach is relatively limited. Furthermore, existing algorithms either rely on networked interactions or lack cognitive strategies for the surrounding communication countermeasure situation. For example, they fail to adapt to dynamic changes in electromagnetic noise and struggle to determine jamming effectiveness, leading to low jamming efficiency and severe energy waste in non-networked scenarios. To address this issue, this paper establishes a game process and corresponding algorithm for non-networked communication countermeasures and designs cognitive, cooperative, and scheduling strategies for individual jammers. Meanwhile, a novel performance metric called the “Overall Communication Suppression Ratio (OCSR)” is proposed. This metric quantifies the relationship between “sustained full-suppression duration” and “ operating duration of the jamming system,” overcoming the defect that traditional metrics cannot evaluate the dynamic jamming effectiveness in non-networked scenarios. Experimental results indicate that although the OCSR of the proposed Intelligent Concentric Circle Algorithm (ICCA) is significantly lower than that of the Full-Power Jamming Algorithm (FPJA), ICCA extends the operating duration of the jamming system by 4.8%. This achieves non-uniform power setting of jammers, enabling flexible and dynamic jamming in non-networked scenarios and retaining more battery capacity for jammers after overall jamming failure.

Automatic modulation recognition (AMR) is a key technique in modern communications. We propose LM-GDMAF, which integrates lightweight Mamba modules with a GDMAF fusion module. The lightweight Mamba modules efficiently extract temporal features, while GDMAF deeply fuses dual-modality information from IQ time series and frequency-domain spectrograms. On a public dataset, the proposed method improves average recognition accuracy by at least 4.25% compared to baseline methods. The number of computational parameters of the lightweight Mamba module is reduced by approximately 26.1% compared to the standard Mamba model. The complete model achieves average modulation recognition accuracy gains of approximately 11.89% and 14.74% over the respective single-branch models.

The strong electromagnetic interference environment on the battlefield has brought new challenges to the networking collaboration of jammers and the estimation of jamming effects. Traditional successful jamming indicators are difficult to meet the needs of continuous, low-power, and flexible jamming, causing difficulties in emergency scheduling of jamming resources. Aiming at the overall degradation of the communication party’s signal reception quality, this paper proposes the restrictive conditions of “overall limited jamming” and the analysis and evaluation index of “multistage jamming-to-signal ratio (J/S)”, which meets the scheduling requirements of distributed jamming resources in harsh environments. Based on the jammer layout that can achieve overall high-intensity jamming, the electromagnetic environment estimation, power scheduling, and collaboration strategies of jammers are designed, a communication countermeasure game algorithm under blocked networking collaboration is established, and the independent dynamic scheduling of jamming resources is realized. The experimental results show that the Concentric Circle Broadcasting Algorithm (CCBA) not only maintains effective communication jamming (the proportion of high-intensity jamming is no less than 50%, and the proportion of normal signal reception of communication nodes is no more than 6%), but also extends the system operation duration by 66.8–269.6% compared with the comparative algorithms for the 600 MHz fixed-frequency and 1 MHz bandwidth communication system. This work is limited to the line-of-sight (LOS) scenario, and future research will extend it to non-line-of-sight (NLOS) scenarios.