基于隐马尔可夫模型的多频率线跟踪算法 ,能在很低的SNR环境下工作 ,但量化误差较大 ,和计算量大 .本文提出另一种选择量测向量和计算量测概率的方法 ,创造条件减小量化误差 .又经简单论证 ,将EM算法和HMM用于多频率线跟踪 ,严格地 (而不是启发式地 )得到EM HMM算法 ,可以极大地减少计算量 .本文又提出获得初始估计以启动EM HMM算法的二种方法 .仿真计算表明 ,所提的算法是有效的 Hidden Markov Model based multi-frequency line tracking algorithm can work in very low SNR environment, but with large quantization error and large amount of calculation.This paper presents another method of selecting measurement vectors and calculating measurement probabilities , To create the conditions to reduce the quantization error.After a simple argument, EM algorithm and HMM for multi-frequency line tracking, strictly (but not heuristically) EM HMM algorithm can greatly reduce the amount of computation.This paper also proposed to obtain The initial estimation starts with two methods of the EM HMM algorithm. Simulation results show that the proposed algorithm is effective