CRLS算法在智能天线中的应用

An Application of Constrained Recursive Least Squares Algorithm for Smart Antennas

提出一种应用于窄带自适应波束形成的约束递归最小二乘算法。通过最小化阵列的输出功率,算法根据环境能有效的实现自适应,并且维持可视方向的频率响应。这种主瓣对准用户和旁瓣对准干扰的能力对当前和未来传感器网络有很大影响。递归最小二乘优势在于不需要对大量相关矩阵求逆,递归方程使相关矩阵的逆容易更新。通过matlab进行了仿真,给出了以改变天线数目和改变阵元间距的方向图以及跟踪能力比较图。仿真结果表明,递归最小二乘算法不仅有较好的稳定性,而且算法有较强的跟踪能力。

Constrained Recursive Least Squares （CRLS） algorithm for narrowband adaptive beamforming has been de- rived. This algorithm is capable of efficiently adapting according to the environment and able to maintain the chosen frequency response in the look direction always while minimizing the output power of the array. [t is capabile for the smart antenna systems to track the user with the main lobe and interference with the nulls creates a significant impact on the current and future wireless sensor networks. The adaptability of the algorithm is closely observed for Uniform- ly spaced Linear Array （ULA）. The results are supported by various simulations environments created in MATLAB like varying the number of antenna arrays and varying inter element spacing between the array elements.