Sidelobe Suppression Of Airborne Three-Dimensional Array Antenna Based On Optimization Algorithm

At present, it is generally known that the airborne three-dimensional array antenna is taking a more and more important part in the airborne radar, airborne data link and electronic countermeasure. Consistent with aircraft shape, the pattern synthesis can be obtained by optimizing the parameters of the array with the constraint of the no change of aerodynamic performance and stealth performance. The airborne three-dimensional array antenna has been widely used in airborne/shipborne radar and communication fields. Applied with various optimization algorithms including Lagrange multiplier algorithm, particle swarm optimization(PSO) algorithm and convex optimization algorithm, several key problems such as mathematical model and performance analysis for radiation pattern synthesis of array antenna, side-lobe suppression of three-dimensional array pattern, grating lobe suppression of distributed linear array pattern and side-lobe suppression of airborne distributed three-dimensional array pattern are studied deeply in this paper. The major research work and results of this paper are as follows:(1) The radiation pattern synthesis model of array antenna is established under the condition of the far field and the conversion of array coordinate system and array element coordinate system is given. The expression of pattern synthesis is derived and the form of its matrix is given without considering the mutual coupling. The influencing factors of pattern performance are analyzed based on the synthesis goal of the largest polarized directional coefficient. The simulation results show that the array element type, sub array distance, and array element distribution model take an influence on the pattern performance parameters including directional coefficient, the side-lobe level, and the cross polarization.(2) The sidelobe suppression of three-dimensional array pattern is studied. Multi-objective particle swarm optimization(MOPSO) is applied to solve the multi-objective optimization problem of main radiation synthesis and low side-lobe constraint, and the simulation results demonstrate the validity of the algorithm. An improved MOPSO based on preference information is presented. The improved algorithm can not only reduce the number of particles and the number of iterations, but also improve the convergence performance of the algorithm. A model of convex optimization problem is constructed to solve the multi- objective optimization problem of low sidelobe pattern synthesis for three-dimensional array. With the application of the convex optimization algorithm, the corresponding optimal solution can be obtained according to the corresponding threshold set.(3) The grating lobe suppression of distributed linear array pattern is studied. With a distributed linear array as a model, the effectiveness of MOPSO to suppress the gating lobe is verified. A hybrid optimization algorithm based on particle swarm optimization and convex optimization is given. In the hybrid optimization algorithm, the particle swarm optimization is used as a global optimization algorithm while the convex optimization is used as a local optimization algorithm, and both the array elements' positions and weights are optimized. The simulation results show that better grating lobe suppression can be obtained by the hybrid optimization algorithm. Considering the array manifold mismatch caused by the disturbance such as array element position error, a robust algorithm for grating lobe suppression is presented. The array manifold mismatch correction is given, and the robust convex optimization model is reconstructed. The results show that robust array optimization weights and array optimization design can be obtained.(4) The sidelobe suppression of airborne distributed three-dimensional array pattern is studied. With the airborne three-dimensional array as a model, the pattern radiation performance is analyzed. The simulation results show that the distributed three-dimensional array keeps better radiation performance than circular array and circular cone array while considering the main lobe width, directivity, cross polarization and so on. A sub array partition method based on maximum radiation angle is given to reduce the number of working elements and the energy consumption of the array antenna. Combined with convex optimization algorithm, multi-objective binary particle swarm optimization(MOBPSO) is used to solve the multiple objective problems of array element working status and main side lobe. The pattern side-lobe suppression for different constrained number of working elements can be got by optimizing the array design. In order to increase the diversity of particles optimization, constrained initial working array element status is set as the solution of the population preference based on the hybrid optimization algorithm.