A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (...A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (SMI) and the Normalized Least Mean Square (NLMS) algorithms is described. Simulation results showed that the less complexity MI-NLMS yields 15 dB improvements in interference suppression and 5 dB gain enhancement over LMS algorithm, converges from the initial iteration and achieves 24% BER improvements at cochannel interference equal to 5. For the case of 4-element uniform linear array antenna, MI-NLMS achieved 76% BER reduction over LMS algorithm.展开更多
为了满足预见性巡航控制(predictive cruise control,PCC)系统对重型卡车质量的精度要求,针对传统重型卡车质量估计算法的不足,设计了重型卡车的质量估计系统。开发了基于车辆纵向动力学和基于高精度地图的卡车质量估算策略,采用归一化...为了满足预见性巡航控制(predictive cruise control,PCC)系统对重型卡车质量的精度要求,针对传统重型卡车质量估计算法的不足,设计了重型卡车的质量估计系统。开发了基于车辆纵向动力学和基于高精度地图的卡车质量估算策略,采用归一化最小均方(normalized least mean square,NLMS)算法对估计质量进行了平滑性处理;完成了质量估计系统的硬件设计;搭建了质量估计算法的Simulink模型,采用基于模型设计的方法进行了系统软件的开发;实车验证了整个系统的可靠性以及质量估计算法的精确性。试验结果表明:与实际的卡车质量相比,质量估计系统计算得到的卡车质量的误差在9%以内。展开更多
Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggest...Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggested ways is to use adaptive equalizers. Convergence rate and misadjustment error in adaptive algorithms play important roles in adaptive equalizer performance. In this paper, affine projection algorithm （APA）, selective regressor APA（SR-APA）, family of selective partial update （SPU） algorithms, family of set-membership （SM） algorithms and selective partial update selective regressor APA （SPU-SR-APA） are compared with conventional algorithms such as the least mean square （LMS） in underwater acoustic communications. We apply experimental data from the Strait of Hormuz for demonstrating the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error （MSE） of SR-APA, SPU-APA0 SPU-normalized least mean square （SPU-NLMS）, SPU-SR-APA0 SM-APA and SM-NLMS algorithms decrease in comparison with the LMS algorithm. Also these algorithms have better convergence rates than LMS type algorithm.展开更多
基金Project supported by the IRPA Secretariat, Ministry of Science,Technology and Environment of Malaysia (No. 04-02-02-0029) andthe Zamalah Scheme
文摘A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (SMI) and the Normalized Least Mean Square (NLMS) algorithms is described. Simulation results showed that the less complexity MI-NLMS yields 15 dB improvements in interference suppression and 5 dB gain enhancement over LMS algorithm, converges from the initial iteration and achieves 24% BER improvements at cochannel interference equal to 5. For the case of 4-element uniform linear array antenna, MI-NLMS achieved 76% BER reduction over LMS algorithm.
文摘为了满足预见性巡航控制(predictive cruise control,PCC)系统对重型卡车质量的精度要求,针对传统重型卡车质量估计算法的不足,设计了重型卡车的质量估计系统。开发了基于车辆纵向动力学和基于高精度地图的卡车质量估算策略,采用归一化最小均方(normalized least mean square,NLMS)算法对估计质量进行了平滑性处理;完成了质量估计系统的硬件设计;搭建了质量估计算法的Simulink模型,采用基于模型设计的方法进行了系统软件的开发;实车验证了整个系统的可靠性以及质量估计算法的精确性。试验结果表明:与实际的卡车质量相比,质量估计系统计算得到的卡车质量的误差在9%以内。
文摘Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggested ways is to use adaptive equalizers. Convergence rate and misadjustment error in adaptive algorithms play important roles in adaptive equalizer performance. In this paper, affine projection algorithm （APA）, selective regressor APA（SR-APA）, family of selective partial update （SPU） algorithms, family of set-membership （SM） algorithms and selective partial update selective regressor APA （SPU-SR-APA） are compared with conventional algorithms such as the least mean square （LMS） in underwater acoustic communications. We apply experimental data from the Strait of Hormuz for demonstrating the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error （MSE） of SR-APA, SPU-APA0 SPU-normalized least mean square （SPU-NLMS）, SPU-SR-APA0 SM-APA and SM-NLMS algorithms decrease in comparison with the LMS algorithm. Also these algorithms have better convergence rates than LMS type algorithm.
