Underwater wireless sensor network target tracking method and device based on adaptive transmission power

Abstract

The invention provides an underwater wireless sensor network target tracking method and device based on adaptive transmission power, and relates to the technical field of underwater target tracking. The invention determines a tracking range, divides the tracking range into four areas of equal area, establishes a positioning base station in the central area of ​​each area, sets up a first-layer node on the water surface of the positioning base station position, and sets up a second-layer node under the corresponding water surface; obtains target original position data, ocean interference data and tracking target motion state data according to the node, analyzes the target original position data to obtain tracking target position data, finds the node optimal power according to the ocean interference data, and calibrates the tracking target position data according to the tracking target position data, the node optimal power and the tracking target motion state data; the invention realizes dual calibration of the tracking target by correcting the signal transmission time difference and the node transmission power optimized by the ocean environment, thereby improving the system performance.

Description

Technical Field

[0001] The invention relates to the technical field of underwater target tracking, and in particular to an underwater wireless sensor network target tracking method and device based on adaptive transmission power. Background Art

[0002] With the continuous development of marine science and technology, underwater sensor networks are playing an increasingly important role in the fields of ocean monitoring, ecological research, military reconnaissance and underwater resource development. In these applications, target tracking is one of the core tasks. However, existing technologies face multiple challenges in solving underwater target tracking, mainly reflected in the complexity of signal propagation and the lack of positioning accuracy.

[0003] First, the underwater environment is highly complex, including the physical and chemical properties of seawater such as temperature, salinity, density, and conductivity, all of which directly affect the propagation characteristics of acoustic signals. The propagation speed of acoustic waves in water will be affected by the above factors, so when locating a target, it is impossible to accurately obtain the true position of the target. In addition, flow, eddy currents, and other dynamic changes in the marine environment can also cause signal attenuation and distortion, making the target position data unstable, further reducing the reliability of the system.

[0004] Secondly, existing technologies usually fail to fully consider the time delay in the signal transmission process. This time delay mainly comes from the distance between the target and the receiving node and the changes in the environment, resulting in insufficient real-time performance of the target position. In fast-moving targets or rapidly changing environments, traditional target tracking methods are prone to positioning deviations and even tracking failures. In actual application scenarios, especially for tracking dynamic targets, signal delays can cause system response lags, thereby affecting the timeliness and accuracy of decision-making.

[0005] Furthermore, most underwater tracking systems currently lack adaptability in the layout of sensor nodes and the design of transmission power, and cannot be dynamically adjusted according to environmental changes or target movement. This leads to unstable signal transmission in some complex or harsh underwater environments, resulting in data loss and inconsistency. In addition, traditional methods usually use fixed transmission power and do not make full use of environmental information for adaptive adjustment, resulting in energy waste and low signal transmission efficiency.

[0006] Therefore, in response to these technical issues, improving the real-time, reliability and accuracy of underwater target tracking systems has become the focus and difficulty of current research. New technical methods need to be able to effectively integrate sensor data, consider environmental factors, and dynamically adjust system parameters according to actual conditions to ensure efficient target tracking in complex underwater environments.

[0007] In the prior art, the publication number CN110191422A discloses a target tracking method for an underwater sensor network in the ocean. The method comprises the following steps: uniformly installing hydroacoustic sensors in a monitoring area to establish multiple clusters; establishing a target motion model, activating cluster heads and sensor nodes in a small area where the target is located, and keeping the remaining sensor nodes and cluster heads in a dormant state; applying a particle filter algorithm to track and locate underwater targets; and further determining whether the target has left the underwater monitoring area. If so, the tracking process is terminated. If not, the method continues to determine whether the target is about to leave the small area where the target is located. If the target is about to leave the small area where the target is located, the cluster heads in the small area where the target is currently located will be the target at the last sampling moment. The target state estimation value and variance estimation value are transmitted to the cluster head node activated at the next moment. If the target does not leave the current small area, the cluster head and sensor nodes in the small area where the target is located are activated at the next moment, and the remaining sensor nodes and cluster heads remain in a dormant state. However, the prior art still has defects. The prior art does not take into account the influence of the time difference of signal transmission and the complex ocean environment on the acquired tracking target position coordinates. The time difference of signal transmission may cause delay or deviation in tracking target position positioning, thereby affecting the accuracy of the system. The complex ocean environment will cause signal attenuation, reflection and interference, thereby further reducing the reliability and accuracy of the data.

[0008] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0009] The purpose of the present invention is to provide an underwater wireless sensor network target tracking method and device based on adaptive transmission power to solve the problems raised in the above background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] The underwater wireless sensor network target tracking method based on adaptive transmission power includes the following specific steps:

[0012] Step 1: Determine the tracking range and divide it into four areas of equal area. Establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface.

[0013] Step 2: The four first-layer nodes jointly obtain the tracking target location data, and wake up and activate some of the second-layer nodes according to the tracking target location data;

[0014] Step 3: Obtain ocean disturbance data through awakened and activated secondary nodes, and generate seawater environment disturbance coefficient and adaptive adjustment factor according to the ocean disturbance data;

[0015] Step 4: Calculate the optimal transmission power of the awakened secondary node through the seawater environment interference coefficient and the adaptive adjustment factor, and calculate the optimal transmission power of the activated secondary node according to the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data;

[0016] Step 5: Obtain the motion state data of the tracked target through the activated secondary node; calculate the signal transmission delay time, and generate the target measurement interference coefficient based on the ocean interference data; predict the position coordinates of the tracked target based on the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time.

[0017] Furthermore, the first-layer node is composed of an underwater acoustic communication machine and a position detector; the underwater acoustic communication machine is used to transmit and receive underwater acoustic signals, and the position detector is used to detect and track the target position;

[0018] The sub-layer node is composed of an underwater acoustic communication machine, a conductivity sensor, a temperature sensor, a salinity sensor, a water pressure sensor, a seawater flow speed detector and an environmental noise signal strength detector; the underwater acoustic communication machine is used to transmit and receive underwater acoustic signals, and the conductivity sensor, temperature sensor, salinity sensor, water pressure sensor, seawater flow speed detector and environmental noise signal strength detector are used to obtain the conductivity, temperature, salinity, water pressure, seawater flow speed and environmental noise signal strength of seawater respectively;

[0019] The specific logic for setting the secondary nodes is as follows: obtain the communication radius of the secondary nodes, determine the communication radius as the layout distance between the secondary nodes, set multiple secondary nodes distributed from top to bottom directly below the first node, and the spacing is the layout distance, and the spacing between the top secondary node and the first node is the layout distance, and the spacing between the bottom secondary node and the bottom of the water is not greater than the layout distance, and arrange multiple circles of secondary nodes distributed in annular directions in the form of concentric circles on the horizontal plane with each secondary node as the center of the circle, and the absolute difference in radius between adjacent inner and outer circles is the layout distance, and any secondary node in the outer circle is connected to at least one secondary node in the adjacent inner circle for communication. The specific formula for setting the layout distance is as follows:

[0020] ;

[0021] in, For the layout distance, is the communication radius.

[0022] Furthermore, the logic of awakening and activating the secondary nodes is as follows: a spherical area is generated with the tracking target position data as the center and the layout distance as the radius, and the secondary nodes in the spherical area are activated; a cylindrical area is generated with the tracking target position and the line between the nearest first-layer node as the axis and the layout distance as the radius, and the secondary nodes in the cylindrical area that do not include the activated secondary nodes are awakened;

[0023] The activated sub-layer node is used to collect the motion state data of the tracking target and the ocean interference data at the sub-layer node, and the awakened sub-layer node is used to collect the ocean interference data at the sub-layer node; the motion state data includes the coordinates, speed, and acceleration of the tracking target position; the ocean interference data includes the conductivity, temperature, salinity, water pressure, seawater flow speed, environmental noise signal strength, and phase of the sub-layer node transmission signal.

[0024] Furthermore, the specific logic for generating the seawater environmental interference coefficient and the adaptive adjustment factor is as follows: obtaining ocean interference data, generating the seawater environmental interference coefficient from the conductivity, salinity and water pressure of the seawater, and generating the adaptive adjustment factor according to the environmental noise signal strength and the phase of the secondary node transmission signal;

[0025] The specific formula for generating the seawater environmental interference coefficient is:

[0026] ;

[0027] in, is the seawater environmental interference coefficient, is the sea water pressure, is the salinity of seawater, is the electrical conductivity of seawater;

[0028] The specific formula for generating the adaptive adjustment factor is:

[0029] ;

[0030] in, is the adaptive power regulation factor, is the total number of activated and awakened sub-layer nodes, The second node in the activated and awakened The environmental noise intensity of each sub-layer node, To activate and wake up the secondary node The phase of the signal transmitted by each sub-layer node, is the theoretical phase without multipath effect, The index of the sub-layer node among all sub-layer nodes that are activated and awakened.

[0031] Further, the optimal transmission power of the awakened secondary node is calculated by the seawater environment interference coefficient and the adaptive adjustment factor, and the optimal transmission power of the activated secondary node is calculated according to the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data;

[0032] The specific formula for calculating the optimal transmission power of the awakened secondary node is:

[0033] ;

[0034] in, For the The optimal transmission power of the awakened secondary nodes, For the The seawater environment interference coefficient of the awakened secondary node, is the adaptive power regulation factor, is the initial transmission power of the awakened secondary node, The index of the awakened secondary node.

[0035] The specific formula for calculating the optimal transmission power of the activated secondary nodes is:

[0036] ;

[0037] in, For the The optimal transmission power of activated secondary nodes, is the initial transmission power of the activated secondary node, For the The seawater environment interference coefficient of the activated sub-layer nodes, is the measured tracking target position coordinate, For the The coordinates of the activated sub-layer nodes, The index of the activated sub-layer node.

[0038] Furthermore, the target measurement interference coefficient is generated according to the ocean interference data. The specific formula is as follows:

[0039] ;

[0040] ;

[0041] ;

[0042] in, For along The target measurement interference coefficient in the axial direction, For along The target measurement interference coefficient in the axial direction, For along The target measurement interference coefficient in the axial direction, is the seawater velocity and The angle between the axes, is the seawater velocity and The angle between the axes, is the seawater velocity and The angle between the axes, The velocity of seawater along Axis speed, The velocity of seawater along Axis speed, The velocity of seawater along Axis speed, is the sea water pressure, is the sea water temperature, is the number of activated sub-layer nodes, is the number of awakened sub-layer nodes;

[0043] Calculate the signal transmission delay time according to the tracking target position data, the first-layer node position data closest to the tracking target position, and the signal transmission speed in seawater;

[0044] The specific formula for calculating the signal transmission delay time is:

[0045] ;

[0046] in, is the signal transmission delay time, is the measured tracking target position coordinate, is the coordinate of the first-layer node closest to the tracking target position, is the transmission speed of the signal in seawater; the position coordinates of the tracking target are predicted based on the motion state data of the tracking target, the seawater motion interference coefficient and the signal transmission delay time;

[0047] The specific formula for predicting the tracking target position coordinates is:

[0048] ;

[0049] in, is the predicted tracking target position coordinate, To track the target position coordinates, is the signal transmission delay time, , , The tracking target edges collected for all activated sub-layer nodes are The average speed in the axial direction, , , The tracking target edges collected for all activated sub-layer nodes are The average acceleration along the axis.

[0050] The present invention further provides an underwater wireless sensor network target tracking device based on adaptive transmission power, the device is used to implement the underwater wireless sensor network target tracking method based on adaptive transmission power, specifically comprising:

[0051] The facility preparation module is used to determine the tracking range, divide the tracking range into four areas of equal area, establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface;

[0052] A wake-up and activation module is used to obtain tracking target location data based on the four first-layer nodes, and wake up and activate some secondary-layer nodes based on the tracking target location data;

[0053] A data analysis module is used to obtain ocean disturbance data by awakening and activating the secondary nodes, and generate a seawater environment disturbance coefficient and an adaptive adjustment factor according to the ocean disturbance data;

[0054] The power optimization module is used to obtain the motion state data of the tracked target through the activated secondary node; calculate the signal transmission delay time, and generate the target measurement interference coefficient according to the ocean interference data, and predict the position coordinates of the tracked target according to the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention takes into account that the time difference of signal transmission may cause delay in tracking target position positioning, and calibrates the tracking target position data obtained through time delay, so that the obtained tracking target position information is more accurate.

[0057] The present invention also takes into account the impact of the complex marine environment on signal transmission, and quantifies this impact by generating a seawater environment interference coefficient, and finds the optimal transmission power of the node through the seawater environment interference coefficient, and finally completes the dual calibration of the tracking target through the optimal transmission power. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the overall method flow of the present invention.

[0059] Figure 2 This is a schematic diagram of the overall structure of an underwater wireless sensor network target tracking system.

[0060] Figure 3This is a diagram of the composition of the underwater acoustic communication system.

[0061] Figure 4 It is a schematic diagram of the overall structure of the device of the present invention. DETAILED DESCRIPTION

[0062] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0063] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0064] Example:

[0065] See also Figure 1-4 , the present invention provides a technical solution:

[0066] The underwater wireless sensor network target tracking method based on adaptive transmission power includes the following specific steps:

[0067] Step 1: Determine the tracking range and divide it into four areas of equal area. Establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface.

[0068] The first-layer node is composed of an underwater acoustic communication machine and a position detector; the underwater acoustic communication machine is used to transmit and receive underwater acoustic signals and can also be used to obtain phase information of the transmission signal, and the position detector is used to detect and track the target position;

[0069] The sub-layer node is composed of an underwater acoustic communication machine, a conductivity sensor, a salinity sensor, a temperature sensor, a water pressure sensor, a seawater flow speed detector and an environmental noise signal strength detector; the underwater acoustic communication machine is used to transmit and receive underwater acoustic signals, and the conductivity sensor, temperature sensor, salinity sensor, water pressure sensor, seawater flow speed detector and environmental noise signal strength detector are used to obtain the conductivity, temperature, salinity, water pressure, seawater flow speed and environmental noise signal strength of seawater respectively;

[0070] The hardware architecture of the underwater acoustic communication machine consists of several main parts, including the underwater acoustic transducer, the digital signal processing unit, the transmitting and receiving modules, and the transceiver switching module. The underwater acoustic transducer plays a role similar to that of an antenna, responsible for transmitting and receiving underwater acoustic signals. The digital signal processing unit integrates an analog-to-digital converter (ADC) and a digital-to-analog converter (DAC), which are responsible for the conversion of analog and digital signals during the transmission and reception process. In addition, the underwater acoustic communication machine can be connected to the upper control unit through the universal asynchronous receiver-transmitter (UART) interface to realize internal and external data communication. The underwater acoustic communication machine is also equipped with a voltage conversion circuit to convert the external power supply into different voltage levels suitable for each module. The digital signal processing unit, as the core of the underwater acoustic communication machine, runs a dedicated software system to perform underwater acoustic signal processing tasks such as encoding, decoding, modulation, demodulation and analog-to-digital conversion. The digital signal processing unit here uses a 32-bit microcontroller from STMicroelectronics (STMicroelectronics Group), which has the characteristics of low energy consumption, high performance, low cost, and rich peripheral interface resources.

[0071] The data transmission format is: a data packet has 2-bit flag bit, 8-bit start bit, 2-bit stop bit, M-bit valid data bit and 16-bit cyclic redundancy check bit. The flag bit is at the front of the entire data packet, which can detect whether the received data packet is sent according to the user's agreement; the start bit includes the valid data length, redundant data bit, confirmation character, and data sequence number information. The valid data bit stores the user's real data, which is stored in the form of 8 bits per byte. The information contained in the valid bit is motion status data and ocean interference data; the cyclic redundancy bit is used to check whether there is an error in the transmitted data. The generation of the cyclic redundancy sequence requires querying the CRC16 table. The stop bit indicates that a complete data packet transmission is completed when these two bits of data are received.

[0072] A rectangular coordinate system is established with the center of the water surface in the tracking range as the origin, and the east direction as the Axis direction, with due north as The positive direction of the axis is vertically downward. Positive axis direction.

[0073] The specific logic for setting the secondary nodes is as follows: obtain the communication radius of the secondary nodes, use the communication radius as the layout distance between the secondary nodes, set multiple secondary nodes distributed from top to bottom directly below the first node, and the spacing is the layout distance, and the spacing between the top secondary node and the first node is the layout distance, and the spacing between the bottom secondary node and the bottom of the water is not greater than the layout distance, and arrange multiple circles of secondary nodes distributed in annular directions in the form of concentric circles on the horizontal plane with each secondary node as the center of the circle, and the absolute difference in radius between adjacent inner and outer circles is the layout distance, and any secondary node in the outer circle is connected to at least one secondary node in the adjacent inner circle for communication, and the specific formula for setting the layout distance is as follows:

[0074] ;

[0075] in, For the layout distance, is the communication radius.

[0076] Step 2: The four first-layer nodes jointly obtain the tracking target location data, and wake up and activate some of the second-layer nodes according to the tracking target location data;

[0077] The tracking target position data is obtained using the trilateral measurement method. The specific formula for obtaining the tracking target position data is:

[0078] ;

[0079] ;

[0080] in, To track the target distance The distance between the first-level nodes, For the signal to be transmitted from the tracking target to the The time required for the first-layer node, is the transmission speed of the signal in seawater, is the measured tracking target position, For the First-level node locations, is the first-level node index;

[0081] The logic of awakening and activating the secondary nodes is as follows: a spherical area is generated with the tracking target location data as the center and the layout distance as the radius, and the secondary nodes in the spherical area are activated. A cylindrical area is generated with the tracking target location and the line between the nearest first-layer node as the axis and the layout distance as the radius, and the secondary nodes in the cylindrical area that do not include the activated secondary nodes are awakened;

[0082] The activated sub-layer node is used to collect the motion state data of the tracking target and the ocean interference data at the sub-layer node, and the awakened sub-layer node is used to collect the ocean interference data at the sub-layer node; the motion state data includes the coordinates, speed, and acceleration of the tracking target position; the ocean interference data includes the conductivity, temperature, salinity, water pressure, seawater flow speed, environmental noise signal strength, and phase of the sub-layer node transmission signal.

[0083] Step 3: Obtain ocean disturbance data through awakened and activated secondary nodes, and generate seawater environment disturbance coefficient and adaptive adjustment factor according to the ocean disturbance data;

[0084] The specific logic for generating the seawater environmental interference coefficient and the adaptive adjustment factor is as follows: Obtain ocean interference data, generate the seawater environmental interference coefficient from the conductivity, salinity and water pressure of seawater, and generate the adaptive adjustment factor based on the environmental noise signal strength and the phase of the secondary node transmission signal;

[0085] The specific formula for generating the seawater environmental interference coefficient is:

[0086] ;

[0087] in, is the seawater environmental interference coefficient, is the sea water pressure, is the salinity of seawater, is the seawater conductivity; seawater environmental interference coefficient Reflects the degree of influence of seawater on signal transmission. The smaller the value, the more conducive to signal transmission. , seawater salinity , seawater conductivity The higher the seawater pressure, the greater the probability of signal distortion in seawater. The increase in seawater salinity and seawater conductivity will aggravate the attenuation of signals in seawater. Therefore, the smaller their values ​​are, the more conducive to signal propagation in seawater. The seawater environmental interference coefficient The smaller it is.

[0088] The specific formula for generating the adaptive adjustment factor is:

[0089] ;

[0090] in, is the adaptive power regulation factor, is the total number of activated and awakened sub-layer nodes, The second node in the activated and awakened The environmental noise intensity of each sub-layer node, To activate and wake up the secondary node The phase of the signal transmitted by each sub-layer node, is the theoretical phase without multipath effect, The index of the sub-layer node among all sub-layer nodes that are activated and awakened. Adaptive power adjustment factor It reflects the degree to which the signal transmission power needs to be adjusted. The larger the value, the greater the degree to which the signal transmission power needs to be adjusted. The generation of the adaptive power adjustment factor can provide an important basis for the adaptive adjustment of the underwater node transmission power. The environmental noise intensity of each sub-layer node The larger the value, the greater the degree to which the power needs to be adjusted. The adaptive power adjustment factor The bigger it is, The phase difference of the signal transmission of the activated and awakened sub-layer nodes. The larger the value, the greater the degree to which the power needs to be adjusted. The adaptive power adjustment factor The bigger it is.

[0091] Step 4: Calculate the optimal transmission power of the awakened secondary node through the seawater environment interference coefficient and the adaptive adjustment factor, and calculate the optimal transmission power of the activated secondary node according to the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data;

[0092] The optimal transmission power of the awakened sub-layer node is calculated based on the seawater environment interference coefficient and the adaptive adjustment factor, and the optimal transmission power of the activated sub-layer node is calculated based on the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data;

[0093] The specific formula for calculating the optimal transmission power of the awakened secondary node is:

[0094] ;

[0095] in, For the The optimal transmission power of the awakened secondary nodes, For the The seawater environment interference coefficient of the awakened secondary node, is the adaptive power regulation factor, is the initial transmission power of the awakened secondary node, is the index of the awakened secondary node. The optimal transmission power of the awakened secondary nodes Reflects the total adjustment degree of the corresponding awakened sub-layer node to the transmission signal in order to combat the marine environment. The larger the value, the greater the total adjustment degree of the awakened sub-layer node to the transmission signal in order to combat the marine environment. The initial transmission power of the awakened sub-layer node The power level used by the awakened sub-layer node when it starts transmitting can provide a reference for power regulation; adaptive power adjustment factor Reflects the degree to which the signal transmission power needs to be adjusted. The larger the value, the greater the degree to which the signal transmission power needs to be adjusted, and the greater the optimal transmission power at the corresponding position; The seawater environment interference coefficient of the awakened secondary nodes It reflects the influence of seawater on signal transmission at the corresponding position. The larger the value, the more unfavorable it is for signal transmission. The greater the signal transmission power needs to be adjusted, the greater the optimal transmission power at the corresponding position.

[0096] The specific formula for calculating the optimal transmission power of the activated secondary nodes is:

[0097] ;

[0098] in, For the The optimal transmission power of activated secondary nodes, is the initial transmission power of the activated secondary node, For the The seawater environment interference coefficient of the activated sub-layer nodes, is the measured tracking target position coordinate, For the The coordinates of the activated sub-layer nodes, The index of the activated sub-layer node.

[0099] No. The optimal transmission power of the activated secondary nodes Reflects the total degree of adjustment of the corresponding activated sub-layer node to the transmission signal in order to counter the marine environment. The larger the value, the greater the total degree of adjustment of the activated sub-layer node to the transmission signal in order to counter the marine environment. The initial transmission power of the activated sub-layer node is The power level used by the activated sub-layer node when it starts transmitting, which can provide a reference for power regulation; adaptive power adjustment factor Reflects the degree to which the signal transmission power needs to be adjusted. The larger the value, the greater the degree to which the signal transmission power needs to be adjusted, and the greater the optimal transmission power at the corresponding position; The seawater environment interference coefficient of the awakened secondary node The seawater environment interference coefficient of activated sub-layer nodes It reflects the influence of seawater on signal transmission at the corresponding position. The larger the value, the more unfavorable it is for signal transmission. The greater the signal transmission power needs to be adjusted, the greater the optimal transmission power at the corresponding position.

[0100] Since underwater target tracking involves many sub-layer nodes, these nodes are in different environments and have different initial information, it is necessary to adjust the transmission power of each node to achieve effective and energy-saving signal transmission.

[0101] Step 5: Obtain the motion state data of the tracked target through the activated secondary node; calculate the signal transmission delay time, and generate the target measurement interference coefficient based on the ocean interference data, and predict the position coordinates of the tracked target based on the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time. The specific formula for generating the target measurement interference coefficient based on the ocean interference data is as follows:

[0102] ;

[0103] ;

[0104] ;

[0105] in, For along The target measurement interference coefficient in the axial direction, For along The target measurement interference coefficient in the axial direction, For along The target measurement interference coefficient in the axial direction, is the seawater velocity and The angle between the axes, is the seawater velocity and The angle between the axes, is the seawater velocity and The angle between the axes, The velocity of seawater along Axis speed, The velocity of seawater along Axis speed, The velocity of seawater along Axis speed, is the sea water pressure, is the sea water temperature, is the number of activated sub-layer nodes, is the number of awakened sub-layer nodes; the target measurement interference coefficient reflects the interference degree of seawater and each sub-layer node to the tracking target measurement. The larger the value, the greater the interference degree to the tracking target measurement. The total interference degree of seawater on the target movement. The larger the value, the greater the total interference degree of seawater on the target movement and the greater the interference degree on the tracking target measurement. The total adjustment degree of the activated sub-layer node to the transmission signal in order to counteract the marine environment. The larger its value is, the greater the probability of signal distortion of the activated sub-layer node transmission; the greater the interference degree to the tracking target measurement; The total adjustment degree of the awakened sub-layer node to the transmission signal in order to counteract the marine environment. The larger the value, the greater the probability of signal distortion of the awakened sub-layer node transmission; the greater the interference degree to the tracking target measurement;

[0106] The signal transmission delay time is calculated based on the tracking target location data, the first-layer node location data closest to the tracking target location, and the signal transmission speed in seawater.

[0107] The specific formula for calculating the signal transmission delay time is:

[0108] ;

[0109] in, is the signal transmission delay time, is the measured tracking target position coordinate, is the coordinate of the first-layer node closest to the tracking target position, is the transmission speed of the signal in seawater;

[0110] Predict the position coordinates of the tracking target based on the motion state data of the tracking target, the seawater motion interference coefficient and the signal transmission delay time;

[0111] The specific formula for predicting the tracking target position coordinates is:

[0112] ;

[0113] in, is the predicted tracking target position coordinate, is the tracking target position coordinate with time delay, is the signal transmission delay time, , , The tracking target edges collected for all activated sub-layer nodes are The average speed in the axial direction, , , The tracking target edges collected for all activated sub-layer nodes are The target measurement interference coefficient reflects the interference degree of seawater and each layer node on the tracking target measurement. Therefore, when predicting the target position, it is necessary to subtract , and The interference of seawater and sub-layer nodes on the tracking target measurement is removed in this way.

[0114] Since it takes time for the node to send a signal to the base station for analysis and processing, the tracking target data obtained in the base station is delayed. In order to eliminate the impact of this lag, the present application constructs an underwater target motion model to predict the target's current position to eliminate the impact of this data lag.

[0115] The present invention further provides an underwater wireless sensor network target tracking device based on adaptive transmission power, the device is used to implement the underwater wireless sensor network target tracking method based on adaptive transmission power, specifically comprising:

[0116] The facility preparation module is used to determine the tracking range, divide the tracking range into four areas of equal area, establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface;

[0117] A wake-up and activation module is used to obtain tracking target location data based on the four first-layer nodes, and wake up and activate some secondary-layer nodes based on the tracking target location data;

[0118] A data analysis module is used to obtain ocean disturbance data by awakening and activating the secondary nodes, and generate a seawater environment disturbance coefficient and an adaptive adjustment factor according to the ocean disturbance data;

[0119] The power optimization module is used to obtain the motion state data of the tracked target through the activated secondary node; generate the target measurement interference coefficient and signal transmission delay time according to the ocean interference data, and predict the position coordinates of the tracked target according to the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time.

[0120] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0121] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An underwater wireless sensor network target tracking method based on adaptive transmission power, characterized in that: The specific steps include: Step 1: Determine the tracking range and divide it into four areas of equal area. Establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface. Step 2: The four first-layer nodes jointly obtain the tracking target location data, and wake up and activate some of the second-layer nodes according to the tracking target location data; Step 3: Obtain ocean disturbance data through awakened and activated secondary nodes, and generate seawater environment disturbance coefficient and adaptive adjustment factor according to the ocean disturbance data; Step 4: Calculate the optimal transmission power of the awakened secondary node through the seawater environment interference coefficient and the adaptive adjustment factor, and calculate the optimal transmission power of the activated secondary node according to the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data; Step 5: Obtain the motion state data of the tracked target through the activated secondary node; calculate the signal transmission delay time, and generate the target measurement interference coefficient according to the ocean interference data, and predict the position coordinates of the tracked target according to the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time; The first-layer node is composed of an underwater acoustic communication machine and a position detector; the underwater acoustic communication machine is used to transmit and receive underwater acoustic signals, and the position detector is used to detect and track the target position; The specific logic for setting the secondary nodes is as follows: obtain the communication radius of the secondary nodes, use the communication radius as the layout distance between the secondary nodes, set multiple secondary nodes distributed from top to bottom directly below the first node, and the spacing is the layout distance, and the spacing between the top secondary node and the first node is the layout distance, and the spacing between the bottom secondary node and the bottom of the water is not greater than the layout distance, and arrange multiple circles of secondary nodes distributed in annular directions in the form of concentric circles on the horizontal plane with each secondary node as the center of the circle, and the absolute difference in radius between adjacent inner and outer circles is the layout distance, and any secondary node in the outer circle is connected to at least one secondary node in the adjacent inner circle for communication, and the specific formula for setting the layout distance is as follows: Where D is the layout distance, R C is the communication radius.

2. The underwater wireless sensor network target tracking method based on adaptive transmission power according to claim 1 is characterized in that: The sub-layer node is composed of an underwater acoustic communicator, a conductivity sensor, a temperature sensor, a salinity sensor, a water pressure sensor, a seawater flow speed detector and an environmental noise signal strength detector; the underwater acoustic communicator is used to transmit and receive underwater acoustic signals, and the conductivity sensor, temperature sensor, salinity sensor, water pressure sensor, seawater flow speed detector and environmental noise signal strength detector are used to obtain the conductivity, temperature, salinity, water pressure, seawater flow speed and environmental noise signal strength of seawater respectively.

3. The underwater wireless sensor network target tracking method based on adaptive transmission power according to claim 1 is characterized in that: The logic of awakening and activating the secondary nodes is as follows: a spherical area is generated with the tracking target location data as the center and the layout distance as the radius, and the secondary nodes in the spherical area are activated. A cylindrical area is generated with the tracking target location and the line between the nearest first-layer node as the axis and the layout distance as the radius, and the secondary nodes in the cylindrical area that do not include the activated secondary nodes are awakened; The activated sub-layer node is used to collect the motion state data of the tracking target and the ocean interference data at the sub-layer node, and the awakened sub-layer node is used to collect the ocean interference data at the sub-layer node; the motion state data includes the coordinates, speed, and acceleration of the tracking target position; the ocean interference data includes the conductivity, temperature, salinity, water pressure, seawater flow speed, environmental noise signal strength, and phase of the sub-layer node transmission signal.

4. The underwater wireless sensor network target tracking method based on adaptive transmission power according to claim 1 is characterized in that: The specific logic for generating the seawater environmental interference coefficient and the adaptive adjustment factor is as follows: obtaining ocean interference data, converting the seawater conductivity, salinity, and water pressure into the seawater environmental interference coefficient, and generating the adaptive adjustment factor according to the environmental noise signal strength and the phase of the secondary node transmission signal; The specific formula for generating the seawater environmental interference coefficient is: Among them, Sa is the seawater environmental interference coefficient, Pa is the seawater pressure, Ya is the seawater salinity, and Ed is the seawater conductivity; The specific formula for generating the adaptive adjustment factor is: Among them, WP is the adaptive power adjustment factor, N is the total number of activated and awakened sub-layer nodes, and No j is the environmental noise intensity of the jth sub-layer node among the activated and awakened sub-layer nodes, Ph j is the phase of the signal transmitted by the jth sub-layer node of the activated and awakened sub-layer node, Ph0 is the theoretical phase when there is no multipath effect, and j is the index of the sub-layer node among all the activated and awakened sub-layer nodes.

5. The underwater wireless sensor network target tracking method based on adaptive transmission power according to claim 4 is characterized in that: The optimal transmission power of the awakened sub-layer node is calculated based on the seawater environment interference coefficient and the adaptive adjustment factor, and the optimal transmission power of the activated sub-layer node is calculated based on the seawater environment interference coefficient, the adaptive adjustment factor and the tracking target position data; The specific formula for calculating the optimal transmission power of the awakened secondary node is: PI i =PI0*WP*Sa i Among them, PI i is the optimal transmission power of the i-th awakened secondary node, Sa i is the seawater environment interference coefficient of the i-th awakened secondary node, WP is the adaptive power adjustment factor, PI0 is the initial transmission power of the awakened secondary node, and i is the awakened secondary node index; PI L =PI1*WP*Sa L *(x k -x L ) 2 +(y k -y L ) 2 +(from k -z L ) 2 Among them, PI L is the optimal transmission power of the Lth activated secondary node, PI1 is the initial transmission power of the activated secondary node, Sa L is the seawater environment interference coefficient of the Lth activated sub-layer node, (x k ,y k ,z k ) is the measured tracking target position coordinate, (x L ,y L ,z L ) is the coordinate of the Lth activated sub-layer node, and L is the activated sub-layer node index.

6. The underwater wireless sensor network target tracking method based on adaptive transmission power according to claim 5 is characterized in that: The target measurement interference coefficient is generated based on the ocean interference data. The specific formula is as follows: Among them, RO X The interference coefficient for the target measurement along the X-axis, RO Y The interference coefficient for the target measurement along the Y-axis, RO z is the interference coefficient of the target measurement along the z-axis, θ x is the angle between the seawater velocity and the X-axis direction, θ y is the angle between the seawater velocity and the Y-axis direction, θ Z is the angle between the seawater velocity and the z-axis direction, x w is the velocity of seawater along the X-axis, y w is the velocity of seawater along the Y axis, z w is the speed of seawater flow along the z-axis, Pa is the seawater pressure, T is the seawater temperature, J is the number of activated sub-layer nodes, and B is the number of awakened sub-layer nodes; Calculate the signal transmission delay time according to the tracking target position data, the first-layer node position data closest to the tracking target position, and the signal transmission speed in seawater; The specific formula for calculating the signal transmission delay time is: Among them, t1 is the signal transmission delay time, (x k ,y k ,z k ) is the measured tracking target position coordinate, (x U ,y U ,z U ) is the coordinate of the first-layer node closest to the tracking target position, V s is the transmission speed of the signal in seawater; predict the position coordinates of the tracking target based on the motion state data of the tracking target, the seawater motion interference coefficient and the signal transmission delay time; The specific formula for predicting the tracking target position coordinates is: in, is the predicted tracking target position coordinate, To track the target position coordinates, t1 is the signal transmission delay time, are the average speeds of the tracked target along the x, y, and z axes collected for all activated sub-layer nodes, The average acceleration of the tracked target along the x, y, and z axes collected for all activated sub-layer nodes respectively.

7. An underwater wireless sensor network target tracking device based on adaptive transmission power, characterized in that: The device is used to implement the underwater wireless sensor network target tracking method based on adaptive transmission power according to any one of claims 1 to 6, specifically comprising: The facility preparation module is used to determine the tracking range, divide the tracking range into four areas of equal area, establish a positioning base station at the center of each area, set up a first-layer node on the water surface at the location of the positioning base station, and set up multiple secondary nodes under the water surface; A wake-up and activation module is used to obtain tracking target location data based on the four first-layer nodes, and wake up and activate some secondary-layer nodes based on the tracking target location data; A data analysis module is used to obtain ocean disturbance data by awakening and activating the secondary nodes, and generate a seawater environment disturbance coefficient and an adaptive adjustment factor according to the ocean disturbance data; The power optimization module is used to obtain the motion state data of the tracked target through the activated secondary node; calculate the signal transmission delay time, and generate the target measurement interference coefficient according to the ocean interference data, and predict the position coordinates of the tracked target according to the motion state data of the tracked target, the target measurement interference coefficient and the signal transmission delay time.

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