Detection range prediction for infrared detection systems

1963 ◽  
Vol 51 (10) ◽  
pp. 1327-1336 ◽  
Author(s):  
N.C. Stirling
Keyword(s):  
Infrared Detection ◽  
Detection Range ◽  
Detection Systems

scholarly journals Design of a Microwave Power Detection System in the 5G-Communication Frequency Band

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2674
Author(s):  
Qingying Ren ◽  
Wen Zuo ◽  
Jie Xu ◽  
Leisheng Jin ◽  
Wei Li ◽  
...  
Keyword(s):  
Frequency Band ◽  
Microwave Power ◽  
Communication Systems ◽  
Detection System ◽  
Measurement Sensitivity ◽  
Detection Range ◽  
Detection Systems ◽  
Detection Frequency ◽  
Communication Frequency ◽  
5G Communication

At present, the proposed microwave power detection systems cannot provide a high dynamic detection range and measurement sensitivity at the same time. Additionally, the frequency band of these detection systems cannot cover the 5G-communication frequency band. In this work, a novel microwave power detection system is proposed to measure the power of the 5G-communication frequency band. The detection system is composed of a signal receiving module, a power detection module and a data processing module. Experiments show that the detection frequency band of this system ranges from 1.4 GHz to 5.3 GHz, the dynamic measurement range is 70 dB, the minimum detection power is −68 dBm, and the sensitivity is 22.3 mV/dBm. Compared with other detection systems, the performance of this detection system in the 5G-communication frequency band is significantly improved. Therefore, this microwave power detection system has certain reference significance and application value in the microwave signal detection of 5G communication systems.

Estimation method of infrared detection range for reentry target based on signal-to-clutter ratio

2021 ◽  
Author(s):  
Zihui Zhu ◽  
Wenlin Cai ◽  
Jianhua Li ◽  
Xia Ai ◽  
Lu Gao ◽  
...  
Keyword(s):  
Estimation Method ◽  
Infrared Detection ◽  
Detection Range

scholarly journals Synthesis of algorithm of unmanned aerial vehicle detection by acoustic noise

Doklady BGUIR ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 65-73
Author(s):  
A. D. Puzanau ◽  
D. S. Nefedov
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Acoustic Noise ◽  
Signal To Noise Ratio ◽  
Weather Conditions ◽  
Wind Noise ◽  
Detection Range ◽  
Detection Systems ◽  
A Value ◽  
Coherent Accumulation ◽  
Aerial Vehicle

 The algorithm of detection of acoustic noise provided by an unmanned aerial vehicle (UAV) in the noise background due to wind is synthesized in the article. Creation of the algorithm has been carried out using the Neyman – Pearson lemma. The algorithm assumes a combination of the stages of wind noise coherent compensation and coherent accumulation of UAV’s acoustic noise sound pressure impulses. The coherent accumulation time matches doubled time of fluctuation correlation resulted by experimental research of acoustic noise of different types of  UAVs. Efficiency of the developed algorithm of UAV detection depends on flight velocity, foreshortening, amount of blades and rotor turnovers of UAV as well as weather conditions. For the probability of a false alarm value of 10–4, the probability of correct UAV detection value of 0.9 is provided wherein signal-to-noise ratio has a value of 8 dB. These indicators correspond the detection range of 200 to 300 meters. The obtained results allow discussions about perspective of acoustic UAVs detection systems adaptation. 

scholarly journals Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7379
Author(s):  
Pedro Teixidó ◽  
Juan Antonio Gómez-Galán ◽  
Rafael Caballero ◽  
Francisco J. Pérez-Grau ◽  
José M. Hinojo-Montero ◽  
...  
Keyword(s):  
Fiber Optics ◽  
Weather Conditions ◽  
False Alarms ◽  
Motion Sensors ◽  
Detection Range ◽  
Detection Systems ◽  
Detection And Tracking ◽  
Sensing Technology ◽  
Electromagnetic Detection ◽  
Privacy Issues

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The current solutions available to secure a perimeter (infrared and motion sensors, fiber optics, cameras, radar, among others) have several problems, such as sensitivity to weather conditions or the high failure alarm rate that forces the need for human supervision. The system exposed in this paper overcomes these problems by combining a perimeter security system based on CEMF (control of electromagnetic fields) sensing technology, a set of video cameras that remain powered off except when an event has been detected. An autonomous drone is also informed where the event has been initially detected. Then, it flies through computer vision to follow the intruder for as long as they remain within the perimeter. This paper covers a detailed view of how all three components cooperate in harmony to protect a perimeter effectively, without having to worry about false alarms, blinding due to weather conditions, clearance areas, or privacy issues. The system also provides extra information of where the intruder is or has been, at all times, no matter whether they have become mixed up with more people or not during the attack.

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