A New On-Line/Off-Line Adaptive Antenna Array Beamformer for Tracking the Mobile Targets

Shahriar Shirvani Moghaddam, Mahyar Shirvani Moghaddam

1Digital communications signal Processing Research Lab., Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University (SRTTU), Tehran, Iran.
2Department of Electrical Engineering and Advanced Communication Research Institute, Sharif University of Technology, Tehran, Iran.

DOI: 10.4236/ijcns.2011.45035                

Abstract

An adaptive antenna array system adjusts the main lobe of radiation pattern in the direction of desired signal and points the nulls in the direction of undesired signals or interferers. The essential goal of beamforming is to reduce the complexity of weighting process and to decrease the time needed for adjusting the antenna radiation pattern. In this article a new adaptive weighting algorithm is proposed for both least mean squares (LMS) and constant modulus (CM) algorithms. It is appropriate and applicable for antenna array systems with moving targets and also mobile applications as well as sensor networks. By predicting the relative velocity of source, the next location of the source will be estimated and the array weights will be determined using LMS or CM algorithm before arriving to the new point. For the next time associated to the new sampling point, evaluated weights will be used. Furthermore, by updating these weights between two consecutive times the effects of error propagation will be eliminated. Therefore, in addition to reduction in computational complexity at the time of weight allocation, relatively accurate weight allocation can be obtained. Simulation results of this investigation show that the angular error related to both LMS-based and CM-based algorithms is less than the conventional LMS and CM algorithms at different signal to noise ratios (SNRs). On the other hand, due to considering off-line process, online computational complexity of new algorithms is slightly low with respect to previous ones.

Keywords

Beamforming, Adaptive Antenna Array, LMS, CM, Training-Based, Blind

Conflicts of Interest

The authors declare no conflicts of interest.

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