The multi-payload collaborative reconnaissance has become a main operating mode of Unmanned Reconnaissance Aerial Vehicles(URAV) at present and for the future.According to the features of three airborne reconnaissance payloads:electronic reconnaissance device, SAR and tilted CCD camera with long focal length, the factors and indicators that have effect on multi-payload collaborative reconnaissance effectiveness were analyzed, and the model of the multi-payload collaborative reconnaissance effectiveness of UAV was established by using linear weighted algorithm.Finally, the reconnaissance effectiveness of an UAV with combination of any two devices of the three kinds of payloads was calculated out and analyzed under different intensity of electronic countermeasures (ECM) environment, and the availability of the model was proved.

To improve the maneuvering target tracking precision under the clutter background at far distance, a maneuvering target tracking algorithm was proposed based on Unbiased Conversion and Unscented Transformation under the Earth Centered Earth Fixed (ECEF) coordinate system.The measured polar coordinate data of missile-borne radar was transformed into data under NED coordinate system, and then to ECEF coordinate system.The tracking was then implemented under ECEF coordinate system.In this method, the error caused by faraway nonlinear coordinate transformation was reduced by using Unbiased Conversion and Unscented Transformation.Maneuvering target tracking precision was further improved by using IMM algorithm.Simulation results show that the proposed method has higher tracking precision compared with the tracking under NED coordinate system.

To make the cost of a mission minimum, the scouting mission planning system of a UAV should decide the height, velocity, time and payload of the UAV based on the its capability, payloads, the mission information and threat information.We established a cost function according to the scouting mission of the UAV, and obtained the weighted sum to each factor by using analytic hierarchy process (AHP).Then, we built up the corresponding models for each factor, and obtained the scouting mission plan of the UAV by simulation.This plan can make a UAV more effective in mission executing.

In complex background scene, the variation of brightness or contrast may affect the performance of image segmentation.To deal with this problem, a new algorithm for image segmentation was proposed based on phase information of geometric edges.The algorithm first extracted phase information of edge using Inter-Coefficient Product (ICP) transform, and obtained the image edge using the phase information.Then, according to the phase information and amplitude, a pixel was chosen as the seed of growing process, and the decision criterion was established.Finally, the whole image was segmented by using region growing.The simulation results show that:the proposed method is not influenced by the variation of brightness or contrast, and can implement infrared image segmentation accurately and effectively.The algorithm also helps to avoid missing the edge information of image.

To nonlinear model of guided projectile with some uncertain and unknown aerodynamic parameters, a controller was designed by combining the backstepping with immersion and invariance (I&I).First, a manifold that denotes the parameter estimation error was set up，then its invariance and attractiveness were maintained by the input of controller and parameter adaptive rate so that the estimation error will converge to zero on this manifold．It was not necessary for the parameter estimator to obey the certainty-equivalence principle.Finally, the stability of the closed-loop control system of the projectile was verified by Lyapunov stability theory.The simulation result shows that the proposed control system can accomplish the trajectory control of the angle of attack under the condition of uncertainty of aerodynamic parameters.