A multi-sensor-system cooperative scheduling method for ground area detection and target tracking

A multi-sensor-system cooperative scheduling method for multi-task collaboration is proposed in this paper.We studied the method for application in ground area detection and target tracking.The aim of sensor scheduling is to select the optimal sensors to complete the assigned combat tasks and obtain the best combat benefits.First,an area detection model was built,and the method of calculating the detection risk was proposed to quantify the detection benefits in scheduling.Then,combining the information on road constraints and the Doppler blind zone,a ground target tracking model was established,in which the posterior Carmér-Rao lower bound was applied to evaluate future tracking accuracy.Finally,an objective function was developed which considers the requirements of detection,tracking,and energy consumption control.By solving the objective function,the optimal sensor-scheduling scheme can be obtained.Simulation results showed that the proposed sensor-scheduling method can select suitable sensors to complete the required combat tasks,and provide good performance in terms of area detection,target tracking,and energy consumption control.

Discussion on the application prospect of the transient electromagnetic method based on the dual launcher and mine advanced detection

The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.

Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections

The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts（ECMWF） ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU（central Russia）subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation（AO）, North Atlantic Oscillation（NAO） and Pacific-North American Pattern（PNA）. Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.

Detecting Isolate Safe Areas in Wireless Sensor Monitoring Systems

Wireless sensors are deployed widely to monitor space, emergent events, and disasters. Collected realtime sensory data are precious for completing rescue missions quickly and efficiently. Detecting isolate safe areas is significant for various applications of event and disaster monitoring since valuable real-time information can be provided for the rescue crew to save persons who are trapped in isolate safe areas. We propose a centralized method to detect isolate safe areas via discovering holes in event areas. In order to shorten the detection delay, a distributed isolate safe area detection method is studied. The distributed method detects isolate safe areas during the process of event detection. Moreover, detecting isolate safe areas in a building is addressed particularly since the regular detecting method is not applicable. Our simulation results show that the distributed method can detect all isolate safe areas in an acceptable short delay.

A STATISTICAL ANALYSIS OF SODAR DATA DETECTED IN YANSHAN MOUNTAIN AREA,BEIJING

According to the characteristics of sodar echo,a classified method for temperature stratification is given. By using sodar data observed in Yanshan Mountain area in Beijing,the statistical characteristics for the height of inversion layer,thermal plume,and the depth of mixed layer are compared.Finally,the appearance frequency for stable,unstable and neutral stratification is analyzed.

Design of recognition algorithm for multiclass digital display instrument based on convolution neural network

Digital display instrument identification is a crucial approach for automating the collection of digital display data.In this study,we propose a digital display area detection CTPNpro algorithm to address the problem of recognizing multiclass digital display instruments.We developed a multiclass digital display instrument recognition algorithm by combining the character recognition network constructed using a convolutional neural network and bidirectional variable-length long short-term memory(LSTM).First,the digital display region detection CTPNpro network framework was designed based on the CTPN network architecture by introducing feature fusion and residual structure.Next,the digital display instrument identification network was constructed based on a convolutional neural network using twoway LSTM and Connectionist temporal classification(CTC)of indefinite length.Finally,an automatic calibration system for digital display instruments was built,and a multiclass digital display instrument dataset was constructed by sampling in the system.We compared the performance of the CTPNpro algorithm with other methods using this dataset to validate the effectiveness and robustness of the proposed algorithm.

Application of underdetermined blind source separation in ultra-wideband communication signals

Aiming to the estimation of source numbers, mixing matrix and separation of mixing signals under underdetermined case, the article puts forward a method of underdetermined blind source separation （UBSS） with an application in ultra-wideband （UWB） communication signals. The method is based on the sparse characteristic of UWB communication signals in the time domain. Firstly, finding the single source area by calculating the ratio of observed sampling points. Then an algorithm called hough-windowed method was introduced to estimate the number of sources and mixing matrix. Finally the separation of mixing signals using a method based on amended subspace projection. The simulation results indicate that the proposed method can separate UWB communication signals successfully, estimate the mixing matrix with higher accuracy and separate the mixing signals with higher gain compared with other conventional algorithms. At the same time, the method reflects the higher stability and the better noise immunity.

Potential for energy conservation:A portable desktop paper reusing system for office waste paper

Renewable paper reusing plays a significant role in the sustainable environment under the background of the shortage in forest resources and the pollution from the paper industry.The conventional reusing stream of waste office paper appears to have low reusing rates while consuming massive amounts of energy in intermediate steps.In this study,we developed a novel portable renewable desktop paper reusing system based on font area detection and greyscale sensor.The proposed system consists of two main parts,namely,a greyscale sensor and font area detection model and a polishing mechanism.Acting as an ink mark detector for waste desktop paper,the greyscale sensor and font area detection model can detect the font in the waste desktop paper using an adaptive dynamic compensation schematic.The polishing mechanism will grind the font area of the wasted desktop paper,and this paper reusing processing is non-chemical,energy saving and environmentally friendly.The proposed system is demonstrated through simulations and experimental results,which show that the proposed renewable desktop paper reusing system is portable and is effective for reusing waste office paper in the office.An accuracy of 99.78%is demonstrated in the greyscale sensor and font area detection model,and the average reuse rate of one piece of paper is 2.52 times,verifying that the proposed portable system is effective and practical in renewable desktop paper reusing applications.

Dual-lens beam compression for optical coupling in superconducting nanowire single-photon detectors

The optical coupling of superconducting nanowire single-photon detectors （SNSPDs） has always been restricted to a single-mode fiber for a limited detection area. In this study, for enhancing photon coupling, a dual-lens system operating at 2.2 K was used to compress the beam size on the basis of the Gaussian beam theory and geometric approximation. A magnification of approximately 0.3 was obtained, and a focused spot with diameter of approximately 10 ~m was measured from a multimode fiber. Assisted with the compressed beam, a system efficiency of 55 % （1550 nm） was achieved for a SNSPD with a detection area of 10 μm × 10 μm and 62.5 pm multimode fiber coupling. At the same time, a high speed of 106 MHz was measured with the proposed system. The realization of a highly compressed optical beam reduced the optical coupling requirement and helped maintain a high speed for the SNSPD.