A program for determining the area of the object entering the IR sensor grid, as well as determining the dynamic characteristics

Currently, to evaluate the dynamic characteristics of objects, quite a large number of devices are used in the form of chronographs, which consist of various optical, thermal and laser sensors. Among the problems of these devices, the following can be distinguished: the lack of recording of the received data; the inaccessibility of taking into account the trajectory of the object flying in the sensor area, as well as taking into consideration the trajectory of the object during the approach to the device frame. The signal received from the infrared sensors is recorded in a separate document in txt format, in the form of a table. When you turn to the document, data is read from the current position of the input data stream in the specified list by an argument in accordance with the given condition. As a result of reading the data, it forms an array that includes N number of columns. The array is constructed in a such way that the first column includes time values, and columns 2...N- the value of voltage . The algorithm uses cycles that perform the function of deleting array rows where there is a fact of exceeding the threshold value in more than two columns, as well as rows where the threshold level was not exceeded. The modified array is converted into two new arrays, each of which includes data from different sensor frames. An array with the coordinates of the centers of the sensor operation zones was created to apply the Pythagorean theorem in three-dimensional space, which is necessary for calculating the exact distance between the zones. The time is determined by the difference in the response of the first and second sensor frames. Knowing the path and time, we are able to calculate the exact speed of the object. For visualization, the oscillograms of each sensor channel were displayed, and a chronograph model was created. The chronograph model highlights in purple the area where the threshold has been exceeded.

Adjacent Channel Interference Modeling of Single Vibration Point on Multichannel Dynamic Pressure Sensors

Pulse waves of a radial artery under different pressures applied through a cuff play an important role in disease diagnosis, especially in traditional chinese medicine (TCM). Pulse waves could be collected by a pressure sensor array affixed to an inflatable cuff. During a process of collecting pulse waves, one sensor of a sensor array moves up and down when the sensor is shocked by a pulse wave. Movement of the sensor leads to the passive displacement of other nearby sensors because of a connecting structure between them. Then, vibration signals will be generated by the nearby sensors although these sensors do not receive radial artery pulse waves. These vibration signals considered an interference are usually superimposed on real signals obtained from these nearby sensors and degrade signal quality. The problem mentioned above does not only generally exist in a pressure sensor array attached to a wristband but also is easy to ignore. This paper proposes a novel interference suppression algorithm based on Welch’s method for estimating and weakening adjacent sensor channel interference to overcome the problem. At first, a sensor array attached to an inflatable cuff and a vibration generator is proposed to establish an experimental platform for simplifying the pulse wave collection process. Then, the interference suppression algorithm is proposed according to mechanical analysis and Welch’s method based on the proposed sensor array and vibration generator. Next anti-interference abilities of the algorithm based on a simplified process are evaluated by different vibration frequencies and applied pressures. The anti-interference abilities of the algorithm based on pulse waves of the radial artery are evaluated indirectly. The results show that the novel interference suppression algorithm could weaken adjacent sensor channel interference and upgrade the signal quality.

Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Perfect Observations Simulation Validation

The simulation of observations—a critical Community Global Observing System Simulation Experiment (OSSE) Package (CGOP) component—is validated first by a comparison of error-free simulated observations for the first 24 h at the start of the nature run (NR) to the real observations for those sensors that operated during that period. Sample results of this validation are presented here for existing low-Earth-orbiting (LEO) infrared (IR) and microwave (MW) brightness temperature (BT) observations, for radio occultation (RO) bending angle observations, and for various types of conventional observations. For sensors not operating at the start of the NR, a qualitative validation is obtained by comparing geographic and statistical characteristics of observations over the initial day for such a sensor and an existing similar sensor. The comparisons agree, with no significant unexplained bias, and to within the uncertainties caused by real observation errors, time and space collocation differences, radiative transfer uncertainties, and differences between the NR and reality. To validate channels of a proposed future MW sensor with no equivalent existing spaceborne sensor channel, multiple linear regression is used to relate these channels to existing similar channels. The validation then compares observations simulated from the NR to observations predicted by the regression relationship applied to actual real observations of the existing channels. Overall, the CGOP simulations of error-free observations from conventional and satellite platforms that make up the global observing system are found to be reasonably accurate and suitable as a starting point for creating realistic simulated observations for OSSEs. These findings complete a critical step in the CGOP validation, thereby reducing the caveats required when interpreting the OSSE results.