CN106873626B - Passive positioning and searching system - Google Patents
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Abstract
The invention relates to the technical field of low, small and slow target passive detection and positioning, in particular to a passive positioning and searching system for an unmanned aerial vehicle. When the system is installed on an unmanned aerial vehicle platform to detect a black flying unmanned aerial vehicle, passive all-dimensional detection of a low-altitude suspicious aircraft is realized, a signal processing unit adopts a time delay estimation algorithm to calculate the accurate position of a target, a servo system controls the unmanned aerial vehicle platform to automatically navigate to be close to the target, and destructive ammunition is launched to strike the target within an effective striking range. The system can realize identification, automatic tracking and capturing of suspicious unmanned aerial vehicles in complex environments, and guide the unmanned aerial vehicle platform to automatically track the target through target noise signal analysis and processing, so that the defect that the visual angle of the existing video image tracking technology is limited is overcome, and the data volume of processing is greatly reduced.
Description
Technical Field
The invention relates to the technical field of low, small and slow target passive detection and positioning, in particular to a passive positioning and searching system for an unmanned aerial vehicle.
Background
The background of the related art of the present invention will be described below, but the description does not necessarily constitute the prior art of the present invention.
The low-small slow target is a general name of an aircraft with low flying height, small radar cross section and slow flying speed. The unmanned aerial vehicle, as a representative of the low and slow speed, has an increasing number of illegal intrusion events caused by the unmanned aerial vehicle due to the lack of effective supervision measures. In order to improve the safety of important places, it is very important to strengthen the detection and attack of the 'black flying' unmanned aerial vehicle.
In the aspect of target detection, because unmanned aerial vehicle is small, and is located ground radar detection blind area, conventional ground radar, photoelectricity/infrared detection means all have certain limitation. In the aspect of unmanned aerial vehicle tracking, mainly through the video image information that artifical judgement unmanned aerial vehicle platform camera acquireed, adopt the mode of remote control to track the target. For patent materials such as a system and a method for actively capturing a low-altitude small unmanned aerial vehicle disclosed in the state intellectual property office, the material utilizes a camera carried by an unmanned aerial vehicle platform to acquire target video image information, realizes automatic tracking of a target through a stereo image processing algorithm, but adopts a visual information acquisition means and has a limited visual angle; for three-dimensional positioning of a space target, the image data volume is large, and the processing process is complex. Acoustic detection is a passive, omni-directional detection technique that works with radiated noise generated during the flight of the unmanned aerial vehicle. Because flying height is low, adopt acoustic array detection technique to catch unmanned aerial vehicle rotor noise more easily, because flying speed is slow, be favorable to sound positioning system's stable tracking.
Aiming at the problem of monitoring and tracking illegal invasion of the unmanned aerial vehicle, the invention provides a passive positioning and homing system, which receives rotor noise generated by an aircraft through a microphone array and then completes target identification, space positioning and automatic homing of an unmanned aerial vehicle platform through an internal circuit unit of the system.
Disclosure of Invention
In order to solve the problems of passive detection and automatic tracking of the low-altitude unmanned aerial vehicle, the passive positioning and target-seeking system of the unmanned aerial vehicle is provided, and the unmanned aerial vehicle is detected, identified, tracked and struck by utilizing an acoustic array detection intelligent thunder technology.
In a preferred embodiment according to the present invention, a passive location-finding system includes a microphone array, an early warning circuit unit, a power supply unit, an acoustic signal acquisition circuit, an information processing unit, a servo unit, a central control unit, a target hitting mechanism, and an unmanned aerial vehicle platform; the microphone array is used for acquiring a rotor wing noise signal of a target unmanned aerial vehicle in an area and converting the noise signal into an electric signal; the early warning circuit unit is used for judging target early warning and sending a system starting signal to the central control unit; the power supply unit is used for each stage of system operation and supplies power for each unit; the acoustic signal acquisition circuit is used for preprocessing the noise signals acquired by the microphone array; the information processing unit is used for carrying out data processing on the signals preprocessed by the acoustic signal acquisition circuit, calculating current azimuth information of a target, calculating a tracking route and finally outputting related control quantity parameters to the servo unit and the central control unit; the servo unit is used for adjusting the flight direction of the unmanned aerial vehicle platform, so that the unmanned aerial vehicle platform can approach a target according to an optimal route; the central control unit is used for commanding and controlling the working state of the system in the whole process and controlling the action of the target striking mechanism; the target hitting mechanism is used for effectively capturing the low-altitude suspicious aircraft.
The early warning circuit unit comprises a pre-amplification circuit, a filter circuit, a shaping circuit, a detection circuit and a starting circuit, the early warning circuit unit is in a low-power consumption working mode in an initial state, noise signals acquired by the microphone array are detected by the detection circuit after being amplified, filtered and shaped in sequence, when the amplitude of the noise signals received by the detection circuit exceeds a set threshold value, the detection circuit extracts multiple characteristic quantities of the noise signals through a signal analysis method to perform target identification, and if the noise signals are identified as a target, the starting circuit sends a starting signal to the power supply unit to start the whole system to enable the sound signal acquisition circuit and the information processing unit to start to work.
The sound signal acquisition circuit comprises an amplifying and filtering circuit and an A/D conversion module, wherein a noise signal acquired by the microphone array is processed by the amplifying and filtering circuit, then is input to the A/D conversion module through sampling, and a digital signal containing noise signal characteristics is output to the information processing unit.
The sampling rate of the sampling is obtained from pre-analyzed drone noise signal characteristics.
The information processing unit processes data of the digital signals output by the acoustic signal acquisition circuit to complete parameter calculation related to the target identification, positioning and tracking processes.
The information processing unit calculates the sound path difference of signals received by each sensor in the microphone array, calculates the target distance, the azimuth angle and the pitch angle by utilizing a generalized correlation time delay estimation algorithm, determines the geometric position of the target, calculates the optimal tracking route and outputs related control quantity parameters to the servo unit and the central control unit.
The information processing unit calculates the azimuth information of the noise source in the working area by using a dual-target azimuth estimation method according to the environmental noise signals acquired by the microphone array, so as to eliminate the influence of the base noise of the unmanned aerial vehicle platform.
The servo system is a feedback control system, controls the unmanned aerial vehicle platform to turn according to the control quantity parameters output by the information processing unit, and sends the position information of the unmanned aerial vehicle platform to the information processing unit in real time.
The information processing unit compares the position information of the unmanned aerial vehicle platform fed back by the servo system with the calculated target position information, when the target is in an effective capture range, the information processing unit outputs capture direction angle adjusting parameters to the central control unit, and the central control unit controls the target striking mechanism to rotate so as to adjust the striking angle.
The concrete advantages are that: the invention is a passive positioning system, the sound detection equipment is generally low in price, and
the system has the characteristics of small volume and low power consumption, reduces the high requirement on the storage capacity of the battery by adopting an acoustic measurement mode, and prolongs the endurance time of the unmanned aerial vehicle platform; utilize passive acoustic detection technique to survey black unmanned aerial vehicle that flies, the disguise is good and be difficult for being disturbed. When the system is installed on an unmanned aerial vehicle platform to detect a black flying unmanned aerial vehicle, passive all-dimensional detection of a low-altitude suspicious aircraft is realized, a signal processing unit adopts a time delay estimation algorithm to calculate the accurate position of a target, a servo system controls the unmanned aerial vehicle platform to automatically navigate to approach the target, and destructive ammunition is launched to strike the target within an effective striking range. The system can realize identification, automatic tracking and capturing of suspicious unmanned aerial vehicles in complex environments, and guide the unmanned aerial vehicle platform to automatically track the target through target noise signal analysis and processing, so that the defect that the visual angle of the existing video image tracking technology is limited is overcome, and the data volume of processing is greatly reduced.
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Features and advantages of the present invention are provided in the detailed description that follows, with reference to the accompanying drawings
Will become more readily understood, wherein:
FIG. 1 is a block diagram of a passive location finding system of the present invention;
FIG. 2 is a block diagram of the early warning circuit unit according to the present invention;
FIG. 3 is a flow chart of the system operation of the passive location finder of the present invention;
Detailed Description
Exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The description of the exemplary embodiments is for exemplary purposes only and is in no way intended to limit the invention and its applications or uses referring to fig. 1, which illustrates an illustrative embodiment of the present invention, providing a passive location-finding system comprising a microphone array, an early warning circuit unit, a power supply unit, an acoustic signal acquisition circuit, an information processing unit, a servo unit, a central control unit, a target striking mechanism, and a drone platform; the microphone array is used for acquiring a rotor wing noise signal of a target unmanned aerial vehicle in an area and converting the noise signal into an electric signal; the early warning circuit unit is used for judging target early warning and sending a system starting signal to the central control unit; the power supply unit is used for each stage of system operation and supplies power for each unit; the acoustic signal acquisition circuit is used for preprocessing the noise signals acquired by the microphone array; the information processing unit is used for carrying out data processing on the signals preprocessed by the acoustic signal acquisition circuit, calculating current azimuth information of a target, calculating a tracking route and finally outputting related control quantity parameters to the servo unit and the central control unit; the servo unit is used for adjusting the flight direction of the unmanned aerial vehicle platform, so that the unmanned aerial vehicle platform can approach a target according to an optimal route; the central control unit is used for commanding and controlling the working state of the system in the whole process and controlling the action of the target striking mechanism; the target hitting mechanism is used for effectively capturing the low-altitude suspicious aircraft.
As shown in fig. 2, the early warning circuit unit includes a pre-amplifier circuit, a filter circuit, a shaping circuit, a detection circuit and a start circuit, the early warning circuit unit is in a low power consumption operating mode in an initial state, noise signals obtained by the microphone array are sequentially amplified, filtered and shaped and then detected by the detection circuit, when the amplitude of the noise signals received by the detection circuit exceeds a set threshold, the detection circuit extracts multiple characteristic quantities of the noise signals by a signal analysis method to perform target identification, and if the noise signals are identified as a target, the start circuit sends a start signal to the power supply unit to start the whole system to enable the sound signal acquisition circuit and the information processing unit to start to operate.
It is emphasized that the low power consumption operation state is initially in the initial state. When the amplitude of the received noise signal exceeds a certain threshold value, multiple characteristic quantities of the noise signal are extracted by the detection circuit through multiple signal analysis methods to perform target identification, if the noise signal is identified as a target, the starting circuit outputs a starting signal to the power supply unit, and the whole acoustic measurement intelligent radar system is started. The target striking mechanism is carried by the unmanned aerial vehicle platform to intelligently detect and automatically find the low-altitude flying target within a certain distance range in the process of approaching the target.
Namely, only the early warning circuit unit is in a working state in a standby state, the sound signal acquisition circuit, the information processing unit, the servo unit, the central control unit and the target striking mechanism in the system are in a standby state, and the system is low in energy consumption and high in cruising ability.
The sound signal acquisition circuit comprises an amplifying and filtering circuit and an A/D conversion module, wherein a noise signal acquired by the microphone array is processed by the amplifying and filtering circuit, then is input to the A/D conversion module through sampling, and a digital signal containing noise signal characteristics is output to the information processing unit.
The sampling rate of sampling is obtained by the unmanned aerial vehicle noise signal characteristic of preliminary analysis, and the sampling rate is obtained by the unmanned aerial vehicle noise signal characteristic of preliminary analysis to fully improve system frequency resolution and work efficiency.
The information processing unit processes data of the digital signals output by the acoustic signal acquisition circuit to complete parameter calculation related to the target identification, positioning and tracking processes.
The information processing unit calculates the sound path difference of signals received by each sensor in the microphone array, calculates the target distance, the azimuth angle and the pitch angle by utilizing a generalized correlation time delay estimation algorithm, determines the geometric position of the target, calculates the optimal tracking route and outputs related control quantity parameters to the servo unit and the central control unit.
The information processing unit calculates the azimuth information of the noise source in the working area by using a dual-target azimuth estimation method according to the environmental noise signals acquired by the microphone array, so as to eliminate the influence of the base noise of the unmanned aerial vehicle platform.
For example: the position of the known unmanned aerial vehicle platform is right above the microphone array, the azimuth angle is 0, the pitch angle is 90, and the distance between the sound source of the unmanned aerial vehicle platform and the detection array is known, so that the influence of the noise of the aircraft is eliminated.
The servo system is a feedback control system 5 system which controls the unmanned aerial vehicle platform to turn according to the control quantity parameters output by the information processing unit and sends the position information of the unmanned aerial vehicle platform to the information processing unit in real time.
The servo system commands the aircraft to turn according to the control quantity output by the information processing unit, so that the flight path of the unmanned aerial vehicle platform can accurately change according to the output result of the information processing unit, the flight direction of the unmanned aerial vehicle platform is adjusted in time, the unmanned aerial vehicle platform can be automatically close to a target, manual remote control is not needed, and the workload is reduced.
The information processing unit compares the position information of the unmanned aerial vehicle platform fed back by the servo system with the calculated target position information, when the target is in an effective capture range, the information processing unit outputs capture direction angle adjusting parameters to the central control unit, and the central control unit controls the target striking mechanism to rotate so as to adjust the striking angle.
According to the target position and the flight track of the unmanned aerial vehicle platform, the information processing unit calculates the target attack time and the target attack direction, and the central control unit adjusts the angle of the target hitting mechanism in real time to aim at the target, so that the hit probability is improved.
According to the signal processing flow of the positioning system shown in fig. 3, after a suspicious target is found, an unmanned aerial vehicle (unmanned aerial vehicle platform) is deployed to lift off with a passive positioning device, an early warning circuit unit starts working to detect rotor noise of the suspicious target in a remote low altitude, if a noise signal received by a microphone array is greater than a certain threshold value, target feature analysis is carried out on the signal, and after the type of the signal is identified, the whole acoustic detection circuit system is started to detect the target. The signal processing unit measures the azimuth information of the target, calculates the optimal tracking track, outputs control quantity parameters to the servo mechanism to control the flight direction of the carrier, and guides the carrier to independently approach the target. When the target is in the effective striking range, the central control unit adjusts the ammunition firing angle according to the target azimuth information measured by the signal processing unit, and aims at the target. The cost is low, and the real-time performance is good.
While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the specific embodiments described and illustrated in detail herein, and that various modifications or changes in light thereof may be effected by those skilled in the art without departing from the scope of the invention as defined in the appended claims.
Claims (8)
1. A passive location-finding system, comprising: the system comprises a microphone array, an early warning circuit unit, a power supply unit, an acoustic signal acquisition circuit, an information processing unit, a servo unit, a central control unit, a target striking mechanism and an unmanned aerial vehicle platform; the microphone array is used for acquiring a rotor wing noise signal of a target unmanned aerial vehicle in an area and converting the noise signal into an electric signal; the early warning circuit unit is used for judging target early warning and sending a system starting signal to the central control unit; the power supply unit is used for each stage of system operation and supplies power for each unit; the acoustic signal acquisition circuit is used for preprocessing the noise signals acquired by the microphone array; the information processing unit is used for carrying out data processing on the signals preprocessed by the acoustic signal acquisition circuit, calculating current azimuth information of a target, calculating a tracking route and finally outputting related control quantity parameters to the servo unit and the central control unit; the servo unit is used for adjusting the flight direction of the unmanned aerial vehicle platform, so that the unmanned aerial vehicle platform can approach a target according to an optimal route; the central control unit is used for commanding and controlling the working state of the system in the whole process and controlling the action of the target striking mechanism; the target striking mechanism is used for effectively capturing the low-altitude suspicious aircraft;
the early warning circuit unit comprises a pre-amplification circuit, a filter circuit, a shaping circuit, a detection circuit and a starting circuit, the early warning circuit unit is in a low-power consumption working mode in an initial state, noise signals acquired by a microphone array are detected by the detection circuit after being amplified, filtered and shaped in sequence, when the amplitude of the noise signals received by the detection circuit exceeds a set threshold value, the detection circuit extracts multiple characteristic quantities of the noise signals through a signal analysis method to perform target identification, and if the noise signals are identified as a target, the starting circuit sends a starting signal to a power supply unit to start the whole system to enable the sound signal acquisition circuit and the information processing unit to start to work.
2. A passive location finding system according to claim 1, wherein: the sound signal acquisition circuit comprises an amplifying and filtering circuit and an A/D conversion module, wherein a noise signal acquired by the microphone array is processed by the amplifying and filtering circuit, then is input to the A/D conversion module through sampling, and a digital signal containing noise signal characteristics is output to the information processing unit.
3. A passive position finding system according to claim 2, wherein: the sampling rate of the sampling is obtained from pre-analyzed noise signal characteristics of the drone.
4. A passive position finding system according to claim 2, wherein: and the information processing unit is used for processing data of the digital signals output by the acoustic signal acquisition circuit to complete parameter calculation related to the target identification, positioning and tracking processes.
5. A passive location finding system according to claim 4, wherein: the information processing unit calculates the sound path difference of signals received by each sensor in the microphone array, calculates the target distance, the azimuth angle and the pitch angle by utilizing a generalized correlation time delay estimation algorithm, determines the geometric position of the target, calculates the optimal tracking route and outputs related control quantity parameters to the servo unit and the central control unit.
6. A passive location finding system according to claim 4, wherein: the information processing unit calculates the azimuth information of the noise source in the working area by using a dual-target azimuth estimation method according to the environmental noise signals acquired by the microphone array, so as to eliminate the influence of the base noise of the unmanned aerial vehicle platform.
7. A passive position finding system according to claim 5, wherein: the servo system is a feedback control system, controls the unmanned aerial vehicle platform to turn according to the control quantity parameters output by the information processing unit, and sends the position information of the unmanned aerial vehicle platform to the information processing unit in real time.
8. A passive position finding system according to claim 7, wherein: the information processing unit compares the position information of the unmanned aerial vehicle platform fed back by the servo system with calculated target position information, when a target is in an effective capture range, the information processing unit outputs capture direction angle adjusting parameters to the central control unit, and the central control unit controls the target striking mechanism to rotate so as to adjust the striking angle.
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| CN107566078A (en) * | 2017-09-14 | 2018-01-09 | 成都安则科技有限公司 | A kind of unmanned plane low-altitude defence system |
| CN108762291B (en) * | 2018-03-06 | 2022-01-14 | 西安大衡天成信息科技有限公司 | Method and system for discovering and tracking remote controller of black flying unmanned aerial vehicle |
| CN113203324A (en) * | 2021-05-07 | 2021-08-03 | 武汉汉略达科技股份有限公司 | Anti-unmanned aerial vehicle detection system and control method thereof |
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| US20160091362A1 (en) * | 2014-09-29 | 2016-03-31 | Fredric H. Schmitz | Aircraft flight characteristic measurement |
| CN107110963B (en) * | 2015-02-03 | 2021-03-19 | 深圳市大疆创新科技有限公司 | System and method for detecting aircraft position and velocity using sound |
| CN105550636B (en) * | 2015-12-04 | 2019-03-01 | 中国电子科技集团公司第三研究所 | A kind of method and device of target type discrimination |
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