Networking Radar-Communication Integrated System (RCIS) promises an improved performance of radar and communication system platform by expanding scanning range and sharing information with each other. But equipping RCIS with directional antennas, in return, will worsen network's connectivity. In this paper, we aim to address the problem of neighbor discovery stage in networking process. Then, we are to present a directional neighbor discovery algorithm called scan based networking radar algorithm, or, SBA-RA. The difference between SBA-RA and previous researches which assume no prior knowledge of neighbors, is that SBA-RA makes full use of the approximate location information of neighbors obtained from RCIS platform to accelerate neighbor discovery. What is more, the performance of SBA-RA in RCIS is evaluated, and then compared with Scan-Based Algorithm (SBA) and Completed Random Algorithm (CRA) in terms of time consumption. And the experiments indicate SBA-RA outweighs the others. In the end, future possibilities to improve SBA-RA are discussed.

Due to the overlap of different users’ information requirements for reconnaissance targets, when unmanned aerial vehicles (UAVs), serving multiple users, perform field reconnaissance missions, it is likely to cause repetitive visit to the same targets. To deal with this problem, a reasonable cooperative mission assignment algorithm is needed. By introducing information sharing mechanism with air communication among UAVs, this letter models the mission assignment problem as a vehicle routing problem with air information sharing (VRPAIS), which can efficiently avoid the repetitive visit of targets. An improved piecewise genetic algorithm with integer splitting is proposed to solve VRPAIS in polynomial time. Simulation results show that in the case of high overlap (about 80%) of information requirements, the proposed method is much more energy efficient compared with the traditional Multiple Traveling Salesman Problem (MTSP) based method without information sharing, with an average energy savings rate of 34.2%.

This paper considers a reconnaissance scenario where multiple unmanned aerial vehicles (UAVs) provide services cooperatively for multiple users with different priorities. Although users all expect to acquire their needed information in a short time, the degree of urgency to meet their demands is different when taking their diverse priorities into account. A priority-driven multiuser satisfaction model is designed, where users’ satisfaction is quantified based on their different priorities, information acquisition demands, and the time they obtain their desired information. To ensure high priority users’ fast information acquisition while avoiding excessive delay in low priority users’ information acquisition, a batchwise information backhaul strategy is adopted. In each batch, a UAV is selected as the data ferry through a consultative mechanism to carry information back to users. This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. The simulation results show that compared with traditional path planning algorithms without considering user satisfaction, our proposed algorithm can guarantee faster information acquisition for users with higher priorities, which leads to higher satisfaction. In addition, the applicability of our proposed reconnaissance strategy and path planning algorithm in different situations is also analyzed.

When multiple heterogeneous unmanned aerial vehicles (UAVs) provide service for multiple users in sensor networks, users’ diverse priorities and corresponding priority-related satisfaction are rarely concerned in traditional task assignment algorithms. A priority-driven user satisfaction model is proposed, in which a piecewise function considering soft time window and users’ different priority levels is designed to describe the relationship between user priority and user satisfaction. On this basis, the multi-UAV task assignment problem is formulated as a combinatorial optimization problem with multiple constraints, where the objective is maximizing the priority-weighted satisfaction of users while minimizing the total energy consumption of UAVs. A multipopulation-based cooperation genetic algorithm (MPCGA) by adapting the idea of “exploration-exploitation” into traditional genetic algorithms (GAs) is proposed, which can solve the task assignment problem in polynomial time. Simulation results show that compared with the algorithm without considering users’ priority-based satisfaction, users’ weighted satisfaction can be improved by about 47% based on our algorithm in situations where users’ information acquisition is tight time-window constraints. In comparison, UAVs’ energy consumption only increased by about 6%. Besides, compared with traditional GA, our proposed algorithm can also improve users’ weighted satisfaction by about 5% with almost the same energy consumption of UAVs.

This paper introduces a robust header compression method for mobile ad hoc networks. The node that implements this algorithm won't need to preserve header context while compressing or decompressing the header. When a packet loses or is corrupted, it will not impact following packets because of the independence of the successive compressed headers. This method can be deployed in point to point mode as well as end to end mode

Various information systems adopt different information category standards and description methods even for the same battlefield space. This leads to the heterogeneity of information distributed in different systems, which hinders the information sharing among different systems. In this paper, we adopt the idea of schema mapping and design a framework of realizing heterogeneous information sharing based on content. We design a concept-logic tree model to organize the battlefield situation information and realize the mapping from local concept models in different systems to a global unified concept model. By constructing a unified information space, we realize the centralized organization, storage, and management of entity description information. Then, the information broadcasting mechanism and content based information query mechanism are designed to realize information sharing. Theoretical analysis and experiment results verify the effectiveness of the proposed framework.