通过分析实测法布里-珀罗型半导体激光器(FP-LD)和分布反馈式半导体激光器(DFB-LD)光谱数据特征，提出了一种基于局部最大矩阵的自适应算法，用于检索半导体激光器光谱峰值。建立数据序列的局部最大矩阵，利用矩阵行向量特征修正该矩阵，根据修正后矩阵的列向量特征定位峰值，并进一步修正和补偿峰值位置。该算法具有较强的抗噪能力，整个检索过程无需人为干预，自适应性和稳健性强，满足实时计算的要求。实测数据计算结果表明，该算法与直接比较法、优化的导数法和遗传算法相比，在检验准确率和计算时间方面优势明显，平均检验准确率可达98%，平均计算时间仅为0.12 s，可应用于半导体激光器实测光谱特性实时分析。

A self-adaptive local maximum algorithm for detecting spectral peaks of semiconductor lasers is proposed by analyzing actually measured spectrum characteristics of Fabry-Perot laser diode (FP-LD) and distributed feedback laser diode (DFB-LD), and the algorithm can be used to detect the spectra of laser diodes. In the algorithm, a local maximum matrix of data series is established and is modified with its row vector characteristics, and the peak is located with its column vector characteristics that are further amended and compensated. The algorithm is free from manual operation during the whole searching process, has higher noise-resistance, self-adaptability and robustness, and meets the requirements of real-time computation. Compared with the comparison algorithm, optimized derivative algorithm and genetic algorithm, the local maximum algorithm has obvious advantages in terms of accuracy rate and computation time. The average test accuracy rate reaches 98% while the average computation time is only 0.12 s. The algorithm can be applied to real-time analysis of actually measured spectrum characteristics of semiconductor lasers.