A distributed acoustic target detection system for low, slow and small aircraft detection

Abstract

This invention discloses a distributed acoustic target detection system for detecting low-altitude, slow-moving, and small aircraft, belonging to the field of acoustic measurement. The system includes a master acoustic array node and several slave acoustic array nodes. Each node comprises a microphone array, a positioning module, a communication module, and a data acquisition module. The master acoustic array node processes the data and uses the communication module to wirelessly control the slave nodes to acquire the location and type of the acoustic target. Employing microphone network topology optimization and wireless communication technology, the system collaboratively collects, processes, and senses information about the environment and monitored objects, expanding the detection range and accuracy of the acoustic detection system. It is suitable for detecting, tracking, and identifying low-altitude, slow-moving, and small aircraft in key areas. This effectively improves the direction-finding accuracy, positioning accuracy, and identification accuracy of acoustic target detection, effectively addressing the increasingly serious threat of low-altitude penetration by low-altitude, slow-moving, and small aircraft.

Description

Technical Field

[0001] This invention relates to the field of acoustic measurement, and more specifically to a distributed acoustic target detection system for detecting low-altitude, slow-moving, and small aircraft. Background Technology

[0002] With the rapid development of aviation technology and the rise of the low-altitude economy, the application of various low-altitude, slow-speed, and small aircraft is becoming increasingly widespread. While significantly improving the quality of human life, these aircraft also pose serious threats to public safety. Low-altitude, slow-speed, and small aircraft fly at low altitudes, have slow speeds, and small characteristic dimensions. Radar detection capabilities are limited due to multipath effects and ground clutter, resulting in blind spots at low altitudes and speeds. Optical equipment, affected by weather and environmental factors, cannot effectively monitor these aircraft around the clock. Therefore, the detection of low-altitude, slow-speed, and small aircraft is currently a key, challenging, and hot topic in the field of low-altitude detection.

[0003] Low-altitude, slow-moving, and small aircraft typically rely on propellers and rotors for power. These high-speed rotating propellers and rotors generate strong and distinctive noise, making them easily detectable. Therefore, sound is a crucial component of the acoustic target characteristics of low-altitude, slow-moving, and small aircraft, and acoustic target detection is an important means of detecting them. Currently, single-array acoustic target detection systems suffer from low detection range, direction-finding accuracy, positioning accuracy, and identification accuracy due to their small array aperture and limited number of microphones. By combining multiple acoustic arrays through network topology optimization and wireless communication technology to collaboratively collect, process, and sense information about the environment and monitored objects, forming a distributed acoustic target detection system, the detection range and accuracy of the system can be effectively improved. This expands the coverage of the detection network, enabling effective detection and identification of low-altitude, slow-moving, and small aircraft in key areas such as airports, thereby enhancing the security monitoring and early warning capabilities of these areas. Summary of the Invention

[0004] The purpose of this invention is to network multiple acoustic arrays through network topology optimization and wireless communication technology, so as to collaboratively collect, process and sense information about the environment and monitored objects, thereby solving the problem of low detection accuracy of existing single acoustic arrays. It has the characteristics of improving the detection range, direction finding accuracy, positioning accuracy and recognition accuracy of acoustic targets, and is suitable for the detection and identification of low, slow and small aircraft in key areas such as airports and nuclear power plants.

[0005] This invention is achieved through the following technical solution: A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft includes: A master node controls several acoustic array nodes to acquire data, integrate and store the data. Several acoustic array nodes are used to collect and preprocess information such as sound and geographic location, and transmit the collected information to the master node in real time via wireless communication. Wireless communication between nodes is achieved through a network structure coded using the omnidirectional antenna of the master node and the directional antenna of the acoustic array nodes. The data processing module is used for the acquisition, reception, integration and display of data between the master node and the acoustic array nodes, and performs in-depth data processing to realize the detection, direction finding, positioning, tracking and identification of acoustic targets.

[0006] In the above technical solution, each acoustic array node includes: The GPS module, wireless communication module, data acquisition module, and power supply module are integrated inside the casing. The microphone array and GPS module antenna, located at the top of the casing, can be quickly unfolded and folded into the casing.

[0007] In the above technical solution, the master node includes: The power module, GPS module, wireless communication module, and server are located inside the chassis. The weather module and GPS module antennas, located at the top of the casing, can be quickly unfolded and folded back into the casing.

[0008] In the above technical solution, the microphone arrays of all acoustic array nodes can be networked into a large-aperture synthetic array. The distribution of the microphone array and acoustic array nodes is optimized according to the frequency range of the detection object. The optimization model of the microphone array is as follows: (1) (2) (3) (4) in: For the first The first acoustic array node The spatial coordinates of each microphone , The distributed microphone array contains a total of Each acoustic array node contains [number] acoustic array nodes. One microphone, For the first The first acoustic array node The weight of each microphone; For wavenumber vectors, The wavenumber vector of the incident sound wave is the reference direction; imaginary number symbol; For the microphone array response function; For the first The range of coordinate values ​​for the acoustic array nodes.

[0009] In this invention, formula (1) is mainly used to solve for the microphone position distribution corresponding to the minimum value of the performance evaluation function of the distributed microphone array. Specifically, the optimal value can be solved by the conjugate gradient method or the particle swarm optimization algorithm to obtain the spatial coordinates of the microphones in the distributed microphone array. .

[0010] Formula (2) is the calculation formula for the performance evaluation function of a distributed microphone array, specifically, the wavenumber vector of any incident sound wave in... Integrating the square of the modulus of the distributed microphone array response function within a certain range allows for a comprehensive evaluation of the distributed microphone array's performance. The value represents the sidelobe (false sound source) suppression effect of the distributed microphone array output. The smaller the value, the better the sidelobe suppression, the larger the dynamic range of the distributed microphone array, and the higher the gain.

[0011] Formula (3) This is the response function of a distributed microphone array, primarily used to calculate the response value of the array to a reference incident sound wave within a scanning area. It is a crucial parameter for evaluating the performance of distributed microphone arrays. The specific calculation process is as follows: for a given wavenumber vector... Given a unit intensity reference incident sound wave, and based on a beamforming algorithm, calculate the incident sound wave (wavenumber vector of which is the wave number vector of the waveguide array focused by the distributed microphone array in any direction). The response value of a sound wave incident from any direction, when the wavenumber vector is... = When the values ​​are equal, the response value of the distributed microphone array is the largest; when they are not equal, the response value is smaller.

[0012] The weight value is usually taken as In practical applications, to highlight a particular acoustic array node, its weight can be appropriately increased, such as the first... Each node is important, so , It is a constant greater than 1.

[0013] Formula (4) is used to represent the range of values ​​for the microphone coordinates in a distributed microphone array. The value of is determined by the actual application conditions.

[0014] In the above technical solution, the GPS module adopts the Real-Time Kinematic (RTK) method. A base station of the RTK system is set at the top of the master node, and a rover station of the RTK system is set at the top of the acoustic array node. At least three rover stations are set on each acoustic array node, and the distance between rover stations on the same acoustic array node is not less than 1 meter, in order to achieve high-precision positioning and orientation of the acoustic array node.

[0015] In this invention, the wireless communication module corresponding to data transmission adopts wireless microwave bridge technology. Directional antennas are configured at the acoustic array nodes, and omnidirectional antennas are configured at the main node. The antennas are placed on the top of the casing to achieve long-distance communication. Upon system startup, the wireless communication module of the main node automatically matches with the wireless communication modules of each acoustic array node. The data acquisition module employs multi-channel dynamic data synchronization acquisition technology to achieve synchronous acquisition of microphone signals. The data acquisition synchronization accuracy requirement is no greater than 1μs, and the phase matching degree is less than 0.1°.

[0016] In this invention, the data acquisition channels between each acoustic array node are synchronized using GPS time synchronization. Specifically, the time information of the GPS signal is used to correct and synchronize the clocks of each node.

[0017] In the above technical solution, the data processing module includes two parts: data acquisition and data processing. The data processing includes distributed acoustic array node networking and positioning, data preprocessing, data feature extraction, acoustic target direction finding, acoustic target positioning and tracking, and acoustic target recognition.

[0018] In this invention, the data acquisition section is mainly used to control the master node and acoustic array nodes to collect and transmit data as required, and to receive, integrate, and display the collected sound, GPS, and meteorological data. The data processing section mainly performs in-depth processing on the sound, GPS, and meteorological data to achieve the detection, direction finding, positioning, tracking, and identification of acoustic targets.

[0019] In the above technical solution, the distributed array node networking localization includes: using the RTK method to distribute all acoustic array nodes and the master node into a network, constructing a larger aperture distributed acoustic target detection array in a unified coordinate system with the master node as the origin. The distributed acoustic array networking localization model is as follows: in, For the first The coordinates of the center of the acoustic array node , , The first Coordinates measured by three RTK rover stations in the acoustic array node; The equation coefficients for the plane containing the three RTK rover stations are as follows: These coordinates are defined relative to the master node's reference station (coordinate origin). Due to positioning errors in the RTK system, the above linear equation cannot be solved directly. Instead, the least squares method can be used to solve the following function to obtain the coordinates of the acoustic array node center.

[0020] Where k is a natural number.

[0021] After obtaining the coordinates of the acoustic array node center relative to the RTK system base station (coordinate origin) of the master node, the position coordinates of the acoustic array node and the coordinates of each microphone on it are obtained based on the geometry of the acoustic array node and the positioning results of the RTK rover. This provides high-precision microphone position coordinates for subsequent data processing, thereby improving the accuracy of acoustic target detection. The positioning accuracy requirement of the RTK system is better than 1cm ± 1ppm.

[0022] Compared with the prior art, the present invention has the following advantages and beneficial effects: This invention optimizes the structure of a distributed acoustic target detection system, presenting its architecture and data acquisition and processing flow. It constructs an RTK-based distributed acoustic array node networking and positioning model, utilizing RTK system positioning results to construct a larger-aperture distributed acoustic target detection array from multiple acoustic arrays, effectively expanding the equivalent aperture of the acoustic target detection array. A microphone array topology optimization method is proposed to optimize the location of acoustic array nodes and the distribution of microphone arrays on them. GPS timing technology is employed to achieve high-precision synchronous data acquisition across channels between distributed acoustic array nodes. This effectively improves the detection range, positioning and tracking accuracy, and recognition accuracy of the distributed acoustic target detection array, expanding the coverage of the acoustic target detection network. The system has a simple and reliable structure, and its data processing method has a clear logic. It can be used for low-altitude detection and early warning in key areas such as airports and nuclear power plants, effectively addressing the increasingly serious low-altitude flight safety threat posed by slow and small aircraft. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a schematic diagram of a distributed acoustic target detection system for detecting low-altitude, slow-moving, and small aircraft. Figure 2 This is a schematic diagram of the acoustic array node of a distributed acoustic target detection system; Figure 3 This is a schematic diagram of the master node of a distributed acoustic target detection system; Figure 4 This is a flowchart of data acquisition and processing for a distributed acoustic target detection system.

[0024] In the diagram: 1 is the first acoustic array node, 2 is the second acoustic array node, 3 is the third acoustic array node, 4 is the fourth acoustic array node, 5 is the fifth acoustic array node, 6 is the master node, 7 is the data processing server, 8 is the data acquisition and processing software, 9 is the microphone array, 10 is the microphone, 11 is the RTK rover antenna, 12 is the acoustic array wireless communication module, 13 is the data acquisition module, 14 is the power module, 15 is the acoustic array node housing, 16 is the housing support leg, 17 is the master node wireless communication module, 18 is the weather module, 19 is the server, 20 is the power module, 21 is the RTK base station antenna, and 22 is the housing. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0026] Example 1 like Figure 1 As shown, the distributed acoustic target detection system in this embodiment includes a master node 6, five acoustic array nodes (node ​​1, node 2, node 3, node 4, and node 5), and data acquisition and processing software 8. The acoustic array nodes communicate with the master node 6 wirelessly. Each acoustic array node measures acoustic signals and node position coordinates via a microphone array 9 and a GPS module, respectively, and continuously transmits the collected information to the master node 6 wirelessly. The master node 6 controls the acoustic array nodes to operate as required, receives signals from the acoustic array nodes, collects local meteorological information, and integrates and stores the signals as required. The data acquisition and processing software 8 is responsible for controlling the master node and each acoustic array node to operate as required, receiving, integrating, and displaying the collected sound, GPS, and meteorological data, and performing in-depth data processing to obtain the location and type of the acoustic target.

[0027] Acoustic array node structure as follows Figure 2As shown, the system includes components such as a microphone array 9, a GPS module, an acoustic array wireless communication module 12, a data acquisition module 13, a power supply module 14, and a housing 15 for the acoustic array nodes. The microphone array 9 is mounted on the top of the housing, with the microphones 10 distributed according to the noise characteristics of the acoustic target. The RTK rover antenna 11 of the GPS module is mounted at the end of the horizontal support rod of the microphone array. Each acoustic array node has four RTK rover antennas, with a distance greater than 1m between them to ensure the positioning and direction-finding accuracy of the GPS module. The acoustic array wireless communication module 12 is located in the upper part of the housing, with its directional antenna located on top. The power supply module 14, being the heaviest component, is located at the bottom of the housing. The data acquisition module 13 is for synchronous... The data acquisition device is located above the power module; the acoustic array wireless communication module 12, data acquisition module 13, and power module 14 are housed inside the casing, which is equipped with support legs 16 to prevent tipping; the microphone array 9, GPS module, acoustic array wireless communication module 12, and data acquisition module 13 are connected to the power module 14 via wires, and the microphone array 9, GPS module, and acoustic array wireless communication module 12 are connected to the data acquisition module 13 via measurement cables; all cables and key parts of the acoustic array node are waterproofed and dustproofed, achieving an IP65 waterproof and dustproof rating.

[0028] The master node structure is as follows Figure 3 As shown, the system includes a main node wireless communication module 17, a meteorological module 18, a server 19, a power module 20, an RTK base station antenna 21 for the GPS module, and a housing 22. The omnidirectional antenna of the main node wireless communication module 17, the RTK base station antenna 21 of the meteorological module 18, and the GPS module are mounted on the top of the housing via extendable and foldable arms. The server 19 and power module 20 are housed inside the housing 22. The main node wireless communication module 17, meteorological module 18, server 19, and GPS module are connected to the power module 20 via wires. The main node wireless communication module 17, meteorological module 18, and GPS module are connected to the mainboard of the server 19 via measurement cables. All cables and critical components of the main node are waterproofed and dustproofed, achieving an IP65 waterproof and dustproof rating.

[0029] The data processing module consists of two parts: data acquisition and data processing, such as... Figure 4 As shown, the data acquisition section is mainly used to control the master node and acoustic array nodes to collect and transmit data according to user requirements, and to receive and integrate the collected sound, GPS, and meteorological data. The data processing section mainly performs in-depth processing on sound, GPS, and meteorological data to achieve acoustic target detection. Specifically, it includes key processes such as distributed acoustic array node networking and positioning, data preprocessing, data feature extraction, acoustic target direction finding, acoustic target positioning and tracking, and acoustic target identification.

[0030] The distributed acoustic array node networking positioning is mainly based on the RTK positioning results of the GPS modules of each acoustic array node and the master node. The calculation basis can refer to the model described in the manual. Construct a distributed acoustic array node position model in a unified coordinate system with the master node as the coordinate origin, solve for the microphone spatial coordinates of each acoustic array node, and construct a larger aperture acoustic target detection array.

[0031] Data preprocessing mainly involves data framing, time-frequency domain filtering, spatial domain filtering, and normalization to enhance the acoustic target signal. Data feature extraction primarily involves calculating time-domain features such as the zero-crossing rate (ZCR) and short-time energy (STE), frequency-domain features such as wavelet transform, cepstral features such as Mel-frequency cepstral coefficients (MFCCs), and deep learning features such as convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Principal component analysis (PCA), independent component analysis (ICA), and deep learning algorithms are then used for data feature dimensionality reduction and extraction to select the acoustic target features to be analyzed, facilitating the selection of acoustic target features and subsequent further analysis.

[0032] Acoustic target direction finding mainly employs beamforming algorithms, minimum variance distortionless response beamforming (MVDR) algorithms, and multiple signal classification algorithms (Music) to calculate the target's direction.

[0033] Acoustic target localization and tracking mainly employs either the Time Difference of Arrival (TDOA) localization algorithm based on a single acoustic array node or the Direction of Arrival (DOA) localization method based on a distributed acoustic array node to calculate the azimuth of the acoustic target, and uses algorithms such as Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) tracking algorithm, and Particle Filter (PF) tracking algorithm for target tracking.

[0034] Sound target recognition mainly uses algorithms such as support vector machine (SVM), backpropagation neural network, and convolutional neural network (CNN) to classify sound targets and identify their types.

Claims

1. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft, characterized in that... include: A master node controls several acoustic array nodes to acquire data, integrate and store the data. Several acoustic array nodes are used to collect and preprocess sound and geographic location information, and transmit the collected information to the master node in real time via wireless communication. The wireless communication between each acoustic array node and the master node is coded and networked by the omnidirectional antenna of the master node and the directional antenna of the acoustic array node. The data processing module is used for the acquisition, reception, integration and display of data between the master node and the acoustic array nodes, and performs in-depth data processing to realize the detection, direction finding, positioning, tracking and identification of acoustic targets.

2. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft according to claim 1, characterized in that... Each acoustic array node includes: The GPS module, wireless communication module, data acquisition module, and power supply module are integrated inside the casing. The microphone array and GPS module antenna, located at the top of the casing, can be quickly unfolded and folded into the casing.

3. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft according to claim 1, characterized in that... The master node includes: The power module, GPS module, wireless communication module, and server are located inside the chassis. The weather module and GPS module antennas, located at the top of the casing, can be quickly unfolded and folded back into the casing.

4. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft according to claim 2 or 3, characterized in that: The GPS module uses a real-time dynamic differential method, setting up a base station of the RTK system at the top of the master node and a rover of the RTK system at the top of the acoustic array node.

5. A distributed acoustic target detection system for detecting low-altitude, slow-moving, and small aircraft according to claim 4, characterized in that: At least three rover stations are set on each acoustic array node, and the distance between rover stations on the same acoustic array node is not less than 1 meter.

6. A distributed acoustic target detection system for detecting low-altitude, slow-moving, and small aircraft according to any one of claims 1-3, characterized in that: The microphone arrays of all acoustic array nodes can be networked into a large-aperture synthetic array. The distribution of the microphone arrays and acoustic array nodes is optimized according to the frequency range of the target object. The optimization model of the microphone array is as follows: in: For the first The first acoustic array node The spatial coordinates of each microphone , N and M are both natural numbers. For the first The first acoustic array node The weight of each microphone; It is a wavenumber vector; The wavenumber vector of the incident sound wave is the reference direction; imaginary number symbol; For the microphone array response function; For the first The coordinate value constraint range of the acoustic array node.

7. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft according to claim 1, characterized in that... The data processing module consists of two parts: data acquisition and data processing. The data processing includes distributed acoustic array node networking and positioning, data preprocessing, data feature extraction, acoustic target direction finding, acoustic target positioning and tracking, and acoustic target recognition.

8. A distributed acoustic target detection system for detecting low-altitude, slow-moving, small aircraft according to claim 7, characterized in that... The distributed array node networking localization includes: using the RTK method to distribute all acoustic array nodes and the master node into a network, constructing a larger aperture distributed acoustic target detection array in a unified coordinate system with the master node as the origin. The distributed acoustic array networking localization model is as follows: in, For the first The coordinates of the center of the acoustic array node , , The first The coordinates measured by the three RTK rover stations in the acoustic array node. These are the equation coefficients for the plane containing the three RTK rover stations.

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