Instrument Landing System （ILS） is a critical navigation device for ensuring flight safety， whose signal quality affects the accuracy and safety of aircraft landing accuracy and safety directly. However， the increasingly complex electromagnetic environment around airports leads to more and more multipath effects， thereby impacting the reliability and precision of ILS signals significantly. Therefore， taking LOCalizer （LOC） as the research object， a signal propagation path analysis method based on backward ray-tracing method was proposed. In the method， by establishing an electromagnetic propagation model of the airport environment and incorporating ray-tracing and path validity determination rules， the propagation characteristics of ILS signals in multipath environments were investigated systematically. And the influence of signal reflection and diffraction effects caused by obstacles on the Difference in Depth of Modulation （DDM） of the airborne LOC receiving signals were particularly analyzed. Simulation results demonstrate that when obstacles are near the runway centerline， DDM experiences significant fluctuations， with the maximum jitter reached 283.4% of the value specified by the International Civil Aviation Organization （ICAO） approximately. And after adjusting the obstacle positions appropriately， occlusions between obstacles and the increased distance between obstacles and the runway centerline lead to a reduction in multipath interference. As a result， the fluctuation of DDM decreases significantly and meets the ICAO’s prescribed limit， with the maximum jitter reached 99.0% of the specified value approximately. The above verifies that this method can assess the impact of multipath propagation on ILS performance in complex airport environments effectively.

The real-valued modified propagator method was proposed to solve the large computational load problem of modified propagator direction of arrival estimation method. This proposed method employed the unitary transformation to rearrange the propagator to be real matrix, which decreased the computational load through the real-valued spectrum peak scanning. And it remained the same estimation performance with modified propagator method. At last, the simulation results confirm that the proposed algorithm can achieve superior estimation precision with lower computational load, compared with modified propagator method, propagator method and multiple signal classification method.

In order to overcome the shortcomings of Covariance Matrix Adaptation Evolution Strategy (CMAES), such as premature convergence and low precision, when it is used in high-dimensional multimodal optimization, a hybrid algorithm combined CMAES with Orthogonal Design with Quantization (OD/Q) was proposed. Firstly, the small population CMAES was used to realize a fast searching. When orthogonal CMAES algorithm trapped in local extremum, base vectors for OD/Q were selected dynamically based on the position of current best solution. Then the entire solution space, including the field around extreme value, was explored by trial vectors generated by OD/Q. The proposed algorithm was guided by this process jumping out of the local optimum. The new approach was tested on six high-dimensional multimodal benchmark functions. Compared with other algorithms, the new algorithm has better searching precision, convergence speed and capacity of global search.