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To solve the combat task assignment of reconnaissance unmanned aerial vehicle (RUAV)/unmanned combat aerial vehicle(UCAV), this paper proposed an efficient task assignment method that takes into account the expected destruction probability of target. This method improves the utility function and constraint of the model that based on the goal of destroying the total sum of the target value. The adjustment factor is added to the model to achieve a balanced distribution of RUAVs/UCAVs resources; the expected destruction probability of target is introduced as a constraint to prevent the excessive distribution of RUAVs/UCAVs resources. Subsequently, a greedy algorithm based on maximizing marginal-return is designed to solve the proposed model. The simulation results show that the improved algorithm not only meets the combat effectiveness but also improves the economic performance on the basis of real-time task allocation.

The air-to-ground missile with strapdown seeker may have the problems, including small field of view(FOV), limited overload, and fall angle constraint. To solve the above mentioned problem, a phased guidance scheme is proposed. In this scheme, the attack trajectory is divided into the following six stages, including glided stage, fall angle constraint stage, target acquisition and adjustment stage, terminal guidance stage and blind zone stage. The glided stage is designed to increase range, the terminal fall angle is attained ahead of time at fall angle constraint stage. The aim of target acquisition and adjustment stage is to adjust the missile attitude, so that the target will fall within the FOV of the seeker. It creates good condition to capture the target for strapdown seeker. In the terminal stage, the guidance law of proportional navigation and attitude track are used to fit the needs of FOV constraint and attack accuracy. The simulation result shows that the project trajectory can solve the application of attacking moving targets for air-to-ground missile with strapdown seeker under multi constraints.

Priori geomagnetic information is important to the geomagnetic navigation. However in practice, the precision of the geomagnetic information is a greatly constraint to the development of the geomagnetic navigation. In order to solve this problem, this paper present a geomagnetic gradient bionic navigation method based on parallel approach without any priori information. Inspired by the evidence that many creatures can navigate using the Earth magnetic field, the navigation process can be considered as a convergence of multi-objective problem, and develop the bionics navigation model. By introducing the parallel approach method to the navigation process, the heading angle can be estimated with the information of magnetic field gradient. The simulation results show the proposed method is able to navigation effectively without magnetic priori information, just rely on the actual geomagnetic measurement, which has implies potential application in the future.