A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave...A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave radar. This method defines a whole-peak-outlier elimination （WPOE） criterion, which is based on in-peak-samples correlation of each target echo spectra, to trim off the target signals and abnormal disturbances with great amplitude from the complex spectra. Therefore, cleaned background noise samples are obtained to improve the accuracy and reliability of noise level estimation. When the background noise is nonhomogeneous, the detection samples are limited and often occupied heavily with outliers. In this case, the problem that the detection threshold is overvalued can be solved. In applications on experimental data, it is verified that this method can reduce the miss alarm rate of signal detection effectively in multiple target situations as well as make the adaptability of the detector better.展开更多
图书馆内书架、墙壁等障碍物会导致射频识别(Radio Frequency Identification,RFID)信号反射、折射,形成多路径效应,使读写器接收到的信号是多个路径信号的叠加,造成信号失真和距离检测偏差。因此,提出基于电子标签距离一致性检测的图...图书馆内书架、墙壁等障碍物会导致射频识别(Radio Frequency Identification,RFID)信号反射、折射,形成多路径效应,使读写器接收到的信号是多个路径信号的叠加,造成信号失真和距离检测偏差。因此,提出基于电子标签距离一致性检测的图书馆内目标图书定位方法。将图书馆内所有图书贴上电子标签,采用小波阈值方法对电子标签接收信号去噪,减少多路径效应产生的干扰,提高接收信号的精准度。以去噪后的电子标签接收信号为基础,选取信号接受强度指标(Received Signal Strength Indicator,RSSI)进行电子标签距离一致性检测。确保在不同距离下,读写器都能准确读取到电子标签反射的接收信号。由此,建立目标图书定位模型。通过读写器读取目标图书和实体参考图书RSSI值确定书架,引入VIRE算法和牛顿插值法计算虚拟图书RSSI值,再根据虚拟图书RSSI值确定目标图书位置,实现图书馆目标图书定位。实验结果表明:所提方法的定位误差始终保持在0.2以下,具有较高的定位准确度,能够在面积大、书本排放密集的图书馆环境中完成目标图书的精准定位。展开更多
This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing...This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing technology. The parameters of the algorithm are also given. Experiments have been conducted, the results show that the algorithm has advantages of high detection probability, simple structure, and excellent real-time performance.展开更多
The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circ...The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.展开更多
文摘A credible method of calculating the detection threshold is presented for the multiple target situations, which appear frequently in the lower Doppler velocity region during the surveillance of sea with HF ground wave radar. This method defines a whole-peak-outlier elimination （WPOE） criterion, which is based on in-peak-samples correlation of each target echo spectra, to trim off the target signals and abnormal disturbances with great amplitude from the complex spectra. Therefore, cleaned background noise samples are obtained to improve the accuracy and reliability of noise level estimation. When the background noise is nonhomogeneous, the detection samples are limited and often occupied heavily with outliers. In this case, the problem that the detection threshold is overvalued can be solved. In applications on experimental data, it is verified that this method can reduce the miss alarm rate of signal detection effectively in multiple target situations as well as make the adaptability of the detector better.
文摘图书馆内书架、墙壁等障碍物会导致射频识别(Radio Frequency Identification,RFID)信号反射、折射,形成多路径效应,使读写器接收到的信号是多个路径信号的叠加,造成信号失真和距离检测偏差。因此,提出基于电子标签距离一致性检测的图书馆内目标图书定位方法。将图书馆内所有图书贴上电子标签,采用小波阈值方法对电子标签接收信号去噪,减少多路径效应产生的干扰,提高接收信号的精准度。以去噪后的电子标签接收信号为基础,选取信号接受强度指标(Received Signal Strength Indicator,RSSI)进行电子标签距离一致性检测。确保在不同距离下,读写器都能准确读取到电子标签反射的接收信号。由此,建立目标图书定位模型。通过读写器读取目标图书和实体参考图书RSSI值确定书架,引入VIRE算法和牛顿插值法计算虚拟图书RSSI值,再根据虚拟图书RSSI值确定目标图书位置,实现图书馆目标图书定位。实验结果表明:所提方法的定位误差始终保持在0.2以下,具有较高的定位准确度,能够在面积大、书本排放密集的图书馆环境中完成目标图书的精准定位。
文摘This paper describes a new method of small moving target detection and analyzes the performance of this algorithm. The method is based on multi-level threshold decision-making and sliding trajectory confidence testing technology. The parameters of the algorithm are also given. Experiments have been conducted, the results show that the algorithm has advantages of high detection probability, simple structure, and excellent real-time performance.
基金Sponsored by The National Natural Science Foundation of China(60872065)Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation(20105152026)State Key Laboratory Open Fund of Novel Software Technology,Nanjing University(KFKT2010B17)
文摘The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.
