圆形阵列无线传感器的鸟鸣声检测方法*

针对海岛湿地自然保护区鸟类等发声动物监测困难的问题，开发了基于物联网的圆形阵列无线传感器实时在线监测系统。鉴于保护区现场环境条件的特殊性，为保障传感器系统在野外长期稳定运行，需减少无鸣声数据的传输量来减轻系统负担，该文提出了基于子带能量谱熵比的动态双门限鸟类鸣声端点检测算法，对监测数据的有效鸣声段检测后实时回传到云平台。经过仿真和野外实测数据对比了不同信噪比下的鸣声检测性能，结果表明在暴风雨、风浪等海岛自然环境噪声下，鸟鸣声端点检测算法的准确率达90%以上，基本可实现海岛环境中的有效鸣声端点检测，提升了圆形阵列无线传感器系统的可靠性。

The method of Birdsong detection based on circular array wireless sensor

Aiming at the difficulty of monitoring vocal animals such as birds in island wetlands and other nature reserves, a real-time online monitoring system with circular array wireless sensors based on the Internet of things is developed. In view of the particularity of the on-site environmental conditions in the reserve, to ensure the long-time stable operation of the sensor system, it is necessary to reduce the burden of system by reducing the silent data transmission. This paper proposes a dynamic double-threshold birdsong endpoint automatic detection algorithm based on the sub-band energy spectrum entropy ratio, which can detect the effective birdsong data and then transmit it to the cloud platform in real time. Through simulation and field measurement data, the sound detection capabilities under different signal-to-noise ratios are compared. The results show that the accuracy of the bird''s voice endpoint detection algorithm is over 90% under the natural island noise such as storms, wind and waves, which can basically realize the effective birdsong endpoint detection in the island and improve the reliability of the circular array wireless sensor system.