掌握昆虫迁飞规律对于农业防治和生态学研究具有重大意义,雷达正是检测昆虫迁飞最有效的手段。昆虫回波弱,传统的恒虚警检测(Constant False Alarm Rate,CFAR)算法在低信噪比(Signal To Noise Ratio,SNR)时的检测性能下降;同时昆虫目标...掌握昆虫迁飞规律对于农业防治和生态学研究具有重大意义,雷达正是检测昆虫迁飞最有效的手段。昆虫回波弱,传统的恒虚警检测(Constant False Alarm Rate,CFAR)算法在低信噪比(Signal To Noise Ratio,SNR)时的检测性能下降;同时昆虫目标体积小、飞行速度慢,在距离维和多普勒维的扩展性弱,特征少,在一维距离像上或者距离多普勒域基于深度学习的识别算法效果不佳。针对上述问题,本文提出了基于YOLOv3(You Only Look Once v3)网络的昆虫目标检测算法,通过短时傅里叶变换丰富目标的图像特征,利用图像特征对昆虫目标进行识别,提高了在低SNR下的检测率。进一步通过虚警-目标二元训练策略、目标检测置信度筛选策略降低了算法的虚警率。仿真和实测数据结果表明,所提算法在低SNR下的检测性能优于CA-CFAR算法,验证了算法的有效性。展开更多
Seven sampling sites in each of three biomes (Western Ghats, foothills of Western Ghats and west coast) of south- western India were investigated to study the distribution, abundance and ecology of pill millipedes (Ar...Seven sampling sites in each of three biomes (Western Ghats, foothills of Western Ghats and west coast) of south- western India were investigated to study the distribution, abundance and ecology of pill millipedes (Arthrosphaera) and associated fauna in relation to edaphic features. Abundance and biomass of Arthrosphaera and other millipedes were the highest in Western Ghats, while earthworms were in foothills. Arthrosphaera magna and Arthrosphaera spp. were common in Western Ghats and foothills respectively, while no Arthrosphaera were found in the west coast. None of the sampling sites consisted of more than one species of Arthrosphaera. Biomass of Arthrosphaera, other millipedes and earthworms significantly differed in Western Ghats (P = 9.48 × 10-7) and foothills (P = 1.35 × 10-8), as did the biomass of species of Arthrosphaera (P = 2.76 × 10-7) between Western Ghats and foothills. Correlation analysis revealed that biomass of Arthrosphaera was significantly (P = 0.01, r = 0.45) correlated with soil organic carbon rather than other edaphic fea- tures (pH, phosphate, calcium and magnesium). Distribution pattern, abundance, biomass and ecology of Arthrosphaera of Western Ghats in relation to soil qualities were compared with millipedes of other regions of the world.展开更多
文摘掌握昆虫迁飞规律对于农业防治和生态学研究具有重大意义,雷达正是检测昆虫迁飞最有效的手段。昆虫回波弱,传统的恒虚警检测(Constant False Alarm Rate,CFAR)算法在低信噪比(Signal To Noise Ratio,SNR)时的检测性能下降;同时昆虫目标体积小、飞行速度慢,在距离维和多普勒维的扩展性弱,特征少,在一维距离像上或者距离多普勒域基于深度学习的识别算法效果不佳。针对上述问题,本文提出了基于YOLOv3(You Only Look Once v3)网络的昆虫目标检测算法,通过短时傅里叶变换丰富目标的图像特征,利用图像特征对昆虫目标进行识别,提高了在低SNR下的检测率。进一步通过虚警-目标二元训练策略、目标检测置信度筛选策略降低了算法的虚警率。仿真和实测数据结果表明,所提算法在低SNR下的检测性能优于CA-CFAR算法,验证了算法的有效性。
文摘Seven sampling sites in each of three biomes (Western Ghats, foothills of Western Ghats and west coast) of south- western India were investigated to study the distribution, abundance and ecology of pill millipedes (Arthrosphaera) and associated fauna in relation to edaphic features. Abundance and biomass of Arthrosphaera and other millipedes were the highest in Western Ghats, while earthworms were in foothills. Arthrosphaera magna and Arthrosphaera spp. were common in Western Ghats and foothills respectively, while no Arthrosphaera were found in the west coast. None of the sampling sites consisted of more than one species of Arthrosphaera. Biomass of Arthrosphaera, other millipedes and earthworms significantly differed in Western Ghats (P = 9.48 × 10-7) and foothills (P = 1.35 × 10-8), as did the biomass of species of Arthrosphaera (P = 2.76 × 10-7) between Western Ghats and foothills. Correlation analysis revealed that biomass of Arthrosphaera was significantly (P = 0.01, r = 0.45) correlated with soil organic carbon rather than other edaphic fea- tures (pH, phosphate, calcium and magnesium). Distribution pattern, abundance, biomass and ecology of Arthrosphaera of Western Ghats in relation to soil qualities were compared with millipedes of other regions of the world.
