IR-UWB系统中基于归一化门限的TOA估计

在基于能量检测的脉冲超宽带测距算法中,如何提高测距精度始终是研究热点.提出一种基于门限比较的两步积分到达时间(TOA)估计算法及相应的门限设置算法.考虑到长积分周期门限比较(TC)算法的测距精度低于短周期,在前者基础上重新进行短周期积分检测,构成两步积分TOA估计算法;根据最优归一化门限与能量采样序列最大值均值比(AMMR, advanced maximum energy sample to mean ratio)的函数关系,提出基于AMMR值的门限设置算法(AMMR-TC),实现了最优归一化门限值的设置.由于短积分周期下,AMMR-TC的性能稍弱于基于能量序列最大最小值比的(MMR-TC)算法,提出将AMMR-TC与均值-门限比较(MEAN-TC)相结合的AMMR-MEAN-TC算法.仿真分析结果表明测距精度均有一定提高.

TOA Estimation Based on Normalized Threshold for IR-UWB Systems

The impulse radio-ultra wideband ( IR-UWB) ranging algorithm based on energy detection is widely applied, improving ranging accuracy turns out to be a key point that draws many researchers' at-tentions. A new two-step-integral time of arrival ( TOA) estimation algorithm based on threshold compari-son ( TC ) was proposed, and the corresponding threshold-setting algorithm was also put forward. The ranging accuracy of the TC algorithm for long integration period is lower than that, for short, the two-step-integral TOA estimation algorithm is built up by one more short integration period detection based on long integration period;according to the functional relation between the optimal normalized threshold and ad-vanced maximum energy sample to mean ratio-TC ( AMMR-TC ) is proposed and the optimal normalized threshold is set. Due to the performance of AMMR-TC is worse than maximum to minimum energy sample ratio-TC ( MMR-TC) a little in short integration period, a novel AMMR-MEAN-TC algorithm is put for-ward in the paper by combining the two algorithms above. Simulations indicate that the ranging accuracy had been improved.