Wind power is an attractive clean energy and wind farms increase with very high speed in recent years. However, as a particular obstacle, wind farms may degrade the performance of radio devices in civil aviation obviously. Therefore, wind farms may threaten the flight safety and correct impact assessment of wind farms on radio devices is important to guarantee the safety of civil aviation. In this chapter the potential impact of wind farms on radio devices in civil aviation and a review of the impact assessment procedure and methods of our research group is presented. The radio devices discussed in the chapter include surveillance devices such as primary surveillance radar (PSR) and second surveillance radar (SSR) and radio navigation devices such as very high frequency omnidirectional range (VOR) and instrument landing system (ILS). A wind farm usually comprises several wind turbines with very large size. The proper estimation of the scattering coefficient or radar cross section (RCS) of the wind turbine is of great importance to assess the impact of wind farms correctly. However, the intensity of electromagnetic scattering and the RCS of a wind turbine vary with several factors. Consequently a review of RCS estimation methods for a wind turbine of our research group is also presented in this chapter.

We consider estimating time delays and amplitudes (real-or complex-valued) from the superposition of very closely spaced signals with known shapes. The well—known high resolution MODE (Method Of Direction Estimation) algorithm, which was originally proposed for angle estimation in array processing, is modified and used with our efficient time delay estimation method WRELAX (Weighted Fourier transformand RELAXation based) algorithm to deal with this problem. The proposed method is referred to as MODE-WRELAX. MODE-WRELAX provides better accuracy than MODE and higher resolution than WRELAX. Moreove it can be used for both complex-and real-valued signals (including those with highly oscillatory correlation functions). Numerical results show that the MODE-WRELAX estimates can approach the corresponding Cram6r-Rao bound. Efficient implementation of the algorithm is also discussed.

Power minimisation approach is an effective interference suppression algorithm for satellite navigation systems. It forms automatically deep nulls in the direction-of-arrival (DOA) of interferences without prior information about the DOAs of satellite signals and interferences. However, it cannot provide flat gains for other directions. Thus, the desired satellite signals may be partly suppressed when they locate in the shallow nulls. By combining eigenvalue thresholding method and l1-norm constraint, a new interference suppression algorithm is proposed for satellite navigation systems that would provide approximately flat gains in all directions except that of interferences. However, the l1-norm constraint leads to a non-smooth optimisation problem which cannot be solved by the conventional gradient-based algorithm. After that, by utilising the proximal operator, an iterative algorithm is proposed. The simulations demonstrate the effectiveness of the proposed algorithm.

APES (Amplitude and Phase EStimationl is an adaptive FIR filtering approach introduced recently for complex spectral estimation. For stationary signals, APES can yield more accurate spectral estimates than the widely used Capon and FFT estimators. The authors present a recursive APES algorithm for time-varying spectral analysis, which is computationaly efficient and only involves FFT and simple matrix operations. The recursive APES algorithm is applied to ISAR (inverse synthetic aperture radar) imaging and feature extraction of targets with complex manoeuvring motion. Both numerical and experimental examples are provided to demonstrate the performance of the proposed method.

In order to suppress the multipath interference in global navigation satellite system, two algorithms based on NLS (nonlinear least square) parameter estimation are proposed. Instead of the classic delay lock loop, the first proposed algorithm estimates the parameters of the line of sight signal and the multipath interference in the correlation domain. The NLS cost function is solved by WRELAX (weighted Fourier transform and RELAXation), which decouples the multidimensional optimization problem into a sequence of one-dimensional optimization problems in a conceptually and computationally simple way. In order to further reduce the complexity, the second NLS algorithm utilizing the characteristic of the C/A code is proposed, which estimate the parameters in the data domain. Finally, the two proposed algorithms are compared with the existing multipath interference methods and show excellent performance and less computational burden.