WO2021097593A1

WO2021097593A1 - Positioning and tracking system and method using wireless energy collection

Info

Publication number: WO2021097593A1
Application number: PCT/CN2019/119095
Authority: WO
Inventors: 赵毓斌; 李晓帆; 须成忠
Original assignee: 深圳先进技术研究院
Priority date: 2019-11-18
Filing date: 2019-11-18
Publication date: 2021-05-27

Abstract

The present invention relates to the technical field of mobile positioning. Disclosed are a positioning and tracking system and method using wireless energy collection. The system comprises an energy transmission apparatus, a passive anchor node and a tracking target, wherein the energy transmission apparatus sends wireless energy to the passive anchor node; the passive anchor node takes a received wireless energy signal as a power supply source to form a ranging signal, and sends the ranging signal to the tracking target; the ranging signal comprises the number, position information and sending power of the passive anchor node; and the tracking target is positioned according to the ranging signal, and the distance between same and the passive anchor node is obtained. The present invention uses a wireless energy transmission mode to supply power, so as to ensure that a system can work for a long time and to solve the power distribution problem therein, thereby realizing the optimal positioning precision and minimum power of a system.

Description

Positioning tracking system and method adopting wireless energy collection

Technical field

The present invention relates to the field of mobile positioning technology, and more specifically, to a positioning tracking system and method using wireless energy collection.

Background technique

Location-based services (LBS) are an important application of wireless networks, such as tracking goods in warehouses, medical care in hospitals, and rescue work for life-saving missions. Among the current mobile positioning systems, the IoT positioning system has been widely deployed, especially in places such as indoors, caves, jungles, and factories where GPS signals cannot reach. Due to its inability to penetrate obstacles to detect, compared with the Global Positioning System (GPS), IoT positioning systems are most popular in harsh environments, such as buildings, urban canyons, under tree canopies or caves. The Internet of Things system has the advantages of large-scale, fast implementation, high cost-effectiveness, high positioning accuracy, and simple ranging technology.

Traditionally, positioning systems based on wireless networks are energy-limited, such as sensor networks, which are powered by fixed batteries and have a limited service life. In order to extend the service life, the battery must be replaced or recharged, which may cause inconvenience, cost, or danger. Another solution is to obtain energy from the environment, as it may provide unlimited power for wireless networks or IoT devices. In particular, radio signals radiated through the surroundings serve as a new source of wireless energy collection. Using radio frequency (RF) signals to power devices, these devices can even work without batteries, used in low-power applications, and can provide unlimited energy for IoT systems.

However, the energy supply of IoT nodes always restricts the life of the system. Using battery-powered mode, after a period of time, a large number of Internet of Things must be re-equipped with batteries or recharged, making manual maintenance costs too high. Although there are many energy-saving IoT technologies, none of them can guarantee that the IoT system can continue to work. Especially for the IoT positioning system, the failure of a single node due to the exhaustion of the battery will cause the positioning accuracy to decrease, and the system may even fail to work normally. Therefore, energy has become a bottleneck restricting the IoT positioning system.

The current energy supply technology for the Internet of Things is divided into two aspects, one is energy-saving technology, and the other is the use of wireless charging technology. At present, there are a large number of energy-saving technologies for the Internet of Things. In addition to the use of power line power supply, there is no and it is impossible to guarantee that the Internet of Things nodes can continue to work forever. There are also many technologies for charging IoT devices with wireless charging technology, such as magnetic induction technology, magnetic coupling technology and microwave wireless charging technology, but there is no technology that directly targets IoT positioning systems, let alone wireless charging positioning systems. The technology of resource and energy allocation methods.

Currently, there are many energy-saving technologies for positioning systems, such as how to reduce the sampling frequency, how to reduce the signal transmission power, etc., to reduce the total energy consumption of the system as much as possible while ensuring a certain positioning accuracy. However, the inherent shortcoming of this method is that the capacity of the battery is always a decline process, no matter what energy-saving technology is adopted, the battery will eventually be exhausted, and the battery still needs to be recharged or replaced. Microwave wireless charging technology can charge wireless sensors or low-power IoT devices, and at the same time, by adjusting the power of wireless power, it can maximize the data transmission rate of wireless nodes or IoT devices. However, the disadvantage of this technology is that there is no targeted power allocation design for the specific application requirements of the positioning system. Because the positioning accuracy requirements of the positioning system are different from the data transmission rate, only increasing the data rate cannot achieve the purpose of improving the positioning accuracy.

Summary of the invention

The purpose of the present invention is to solve the technical problems existing in the prior art by providing a positioning and tracking system and method using wireless energy collection, using wireless energy transmission for power supply, ensuring that the system can work for a long time, and solving the power Allocate the problem to achieve the optimal positioning accuracy and minimum power of the system.

In order to solve the above-mentioned problems, the technical solution adopted by the present invention is as follows:

A positioning and tracking system using wireless energy harvesting, the system including an energy transmitting device, a passive anchor node and a tracking target;

The energy transmitting device sends a wireless energy signal to the passive anchor node;

The passive anchor node uses the received wireless energy signal as a power source to form a ranging signal and send it to the tracking target;

The tracking target is positioned according to the ranging signal, and the distance between it and the passive anchor node is obtained.

Further, the energy transmitting device is set to contain K antennas, and form mutually orthogonal signal vectors x=[x ₁ ,...,x _K ] ^T , T represents transposition; wherein the power of each signal is

Where k refers to the k-th antenna, and the value of k is 1 to K, then the power vector of the signal r _x =[r _x ¹ ,...,r _x ^K ] ^T.

Further, there are N passive anchor nodes, and the channel matrix from the energy transmitting device to the passive anchor node is G=[g,...,g _N ] ^T , where each element g _N =[G] _kn Represents the channel attenuation coefficient from the kth antenna to the nth passive anchor node. The value of n is 1～N, then the channel attenuation coefficient vector is g _n =[g _1n ,...,g _kn ]; the defined channel is obtained Gain

Is the mean square of g _kn , the channel gain vector

Further, the next Cramer-Roy is used as the measurement standard of the positioning accuracy of the system, where Cramer-Roy’s next is the inverse matrix of the Fisher matrix; according to the power vector r _x and the channel gain vector of the signal

Construct the Fisher matrix, specifically expressed as formula (1):

among them,

Is the direction angle matrix, φ is the direction angle at which the nth passive anchor node reaches the tracking target,

Background noise variance; d _n is the distance between the target track passive anchor node, 2β is the attenuation factor of the signal propagation.

Further, under the condition of a given signal power, a positive semi-definite programming problem is constructed according to formula (1) to improve the positioning accuracy of the system, and formula (2) is obtained:

Among them, P ₀ is the total power of the transmitted signal.

Furthermore, given the positioning error requirement, formula (2) is described as follows to obtain the minimum transmission power of the system, and formula (3) is obtained:

Among them, ρ ₀ is the positioning error of the tracking target.

Further, construct the matrix inequality J _e ^-1 ≤Z, and then construct

Among them, I is the identity matrix, and Z is the matrix constructed, and then the semi-definite programming problem with the highest positioning accuracy is constructed, and formula (4) is obtained:

Among them, P ₀ is the total power of the transmitted signal.

Furthermore, according to formula (4), the semi-definite programming problem of minimum transmission power is constructed, and formula (5) is obtained:

A positioning and tracking method using wireless energy harvesting, the specific steps of the method are as follows:

Step S1: Set up a positioning and tracking system, including an energy transmitting device, passive anchor nodes and tracking targets. The energy transmitting device sends wireless energy signals to the passive anchor nodes for power supply; the passive anchor nodes form a ranging signal and send it to the tracking target ; The tracking target performs autonomous positioning according to the received ranging signal, and obtains the distance between it and the passive anchor node;

Step S2: Obtain the power vector r _{x of the} signal sent by the energy transmitting device and the channel gain vector between the energy transmitting device and the passive anchor node

Step S3: According to the power vector r _{x of} the signal and the channel gain vector

Construct a Fisher matrix, and use the inverse matrix of the Fisher matrix as the next term of Cramer, and use the next term of Cramer as the measurement standard of the positioning accuracy of the system;

Step S4: Under the condition of a given total power of the signal sent by the energy transmitting device, construct a positive semi-definite programming problem according to the Fisher matrix to improve the positioning accuracy of the system;

Step S5: Under the condition of a given tracking target positioning error requirement, the positive semi-definite programming problem is converted to obtain the minimum transmission power of the system.

Compared with the prior art, the present invention has the following advantages:

The system of the present invention adopts energy transmitting device, passive anchor node and tracking target, that is, based on microwave wireless energy transmission, to supply power to the Internet of Things positioning system, and solves the battery bottleneck problem. In order to improve the positioning accuracy, a positive semi-definite programming problem is constructed to optimize the energy distribution method, so as to maximize the positioning accuracy under the condition of a given transmission power limitation. Furthermore, the positive semi-definite programming problem is converted to minimize the transmission power under the given positioning accuracy requirements.

Description of the drawings

Fig. 1 is a schematic diagram of a positioning and tracking system using wireless energy collection according to the present invention.

Fig. 2 is a flowchart of a location tracking method using wireless energy harvesting according to the present invention.

Description of reference signs: 100-energy transmitting device, 200-passive anchor node, 300-tracking target.

Detailed ways

In order to make the purpose, technical solutions, and advantages of this application clearer, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not used to limit the present application.

Referring to FIG. 1, an embodiment of the present application provides a positioning and tracking system using wireless energy harvesting. The system includes an energy transmitting device 100 (E-AP), a passive anchor node 200 and a tracking target 300.

The energy transmitting device 100 sends a wireless energy signal to the passive anchor node 200.

The passive anchor node 200 uses the received wireless energy signal as a power source to form a ranging signal and send it to the tracking target 300. The ranging signal includes the passive anchor node's number, location information, and transmission power.

The tracking target 300 performs autonomous positioning according to the ranging signal, and obtains the distance between it and the passive anchor node 200.

Further, the energy transmitting device 100 has the functions of wireless energy transmitting and feedback data receiving. It is assumed that it contains K antennas and forms a mutually orthogonal signal vector x=[x ₁ ,...,x _K ] ^T , and T represents rotation. Set; where the power of each signal is

Where k refers to the kth antenna (the value of k is 1 to K), then the power vector of the signal r _x =[r _x ¹ ,..., r _x ^K ] ^T.

The passive anchor node 200 is a wireless node of the Internet of Things that does not contain any power supply or battery equipment. There are N passive anchor nodes 200. The channel matrix from E-AP 100 to the passive anchor node 200 is G=[g, …, g _N ] ^T , where each element g _N =[G] _kn represents the channel attenuation coefficient from the kth antenna to the nth passive anchor node 200, and the value of n is 1～N. Then, the channel attenuation coefficient vector of the kth antenna to the nth passive anchor node 200 is g _n =[g _1n ,..., g _kn ]. And then get the defined channel gain

Is the mean square of g _kn , the channel gain vector

In the embodiments of the present application, the next Cramero is used as the measurement standard of the positioning accuracy of the system, where the next Cramero is the inverse matrix of the Fisher matrix. According to the power vector r _{x of} the signal and the channel gain vector

To construct the Fisher matrix, it can be expressed specifically in formula (1):

among them,

Background noise variance; d _n is the distance between the target track passive anchor node, 2 beta is the attenuation factor of the signal propagation, free space is generally set to 2.

Furthermore, based on the above-mentioned Fisher matrix EFIM, a positive semi-definite programming method is used to optimize the energy allocation method, so as to maximize the positioning accuracy under the condition of a given transmission power limitation. According to formula (1) to construct a positive semi-definite programming problem, refer to formula (2) as shown:

Among them, P ₀ is the total power of the transmitted signal.

Assuming that the system's error requirement for tracking target positioning is ρ ₀ , formula (2) can be described as formula (3):

The above formulas (2) and (3) are typical semi-definite programming problems, and can be solved by many positive semi-definite programming methods, such as interior point methods. The semi-definite programming problem constructed by formula (2) can achieve the highest positioning accuracy of the system under the condition of a given E-AP transmit power. The semi-definite programming problem constructed by formula (3) can achieve the minimum transmission power of the system under the given positioning error requirement.

In another embodiment of the present application, other positive semi-definite programming methods are used for power allocation, and the matrix inequality J _e ^-1 ≤Z is constructed, and then the

Where I is the identity matrix, and Z is the matrix to be constructed, that is, the matrix to be sought, and then the semi-definite programming problem with the highest positioning accuracy is constructed. Refer to formula (4):

According to formula (4), construct the semi-definite programming problem of minimum transmit power, refer to formula (5):

In the embodiment of the present application, the energy transmitting device 100 may also directly send a positioning signal to the tracking target 300, so that the tracking target 300 performs positioning according to the received positioning signal. However, compared with positioning through the passive anchor node 200, the positioning effect is poorer by directly receiving and positioning the signal through the tracking target 300.

Referring to FIG. 2, an embodiment of the present application also provides a positioning and tracking method using wireless energy harvesting, and the specific steps of the method are as follows:

Step S1: Set up a positioning and tracking system, including an energy transmitting device 100, a passive anchor node 200 and a tracking target 300, wherein the energy transmitting device 100 sends wireless energy signals to the passive anchor node 200 for power supply; the passive anchor node 200 forms a ranging The signal is sent to the tracking target 300; the tracking target 300 performs autonomous positioning according to the received ranging signal, and obtains the distance between it and the passive anchor node 200.

Step S2: Obtain the power vector r _x of the energy transmitted by the energy transmitting device and the channel gain vector between the energy transmitting device and the passive anchor node

In this step S2, it is assumed that the energy transmitting device contains K antennas and forms a mutually orthogonal signal vector x=[x ₁ ,...,x _K ] ^T , T represents transposition; wherein the power of each signal is

Where k refers to the kth antenna (the value of k is 1 to K), then the power vector of energy r _x =[r _x ¹ ,..., r _x ^K ] ^T.

There are N passive anchor nodes, and the channel matrix from E-AP to passive anchor node is G=[g,...,g _N ] ^T , where each element g _N ＝[G] _kn means that from the kth The attenuation coefficient of the channel from the antenna to the nth passive anchor node, and the value of n is 1～N. Then the channel attenuation coefficient vector of the kth antenna to the nth passive anchor node is g _n =[g _1n ,..., g _kn ]. And then get the defined channel gain

Is the mean square of g _kn , the channel gain vector

Construct a Fisher matrix, use the inverse matrix of the Fisher matrix as the next Cramero, and use the next Cramero as the measurement standard of the positioning accuracy of the system.

In this step S3, the Fisher matrix can specifically be expressed by referring to formula (1):

among them,

Step S4: Under the condition of a given total power of the energy sent by the E-AP, a positive semi-definite programming problem is constructed according to the Fisher matrix to improve the positioning accuracy of the system.

In this step S4, construct a positive semi-definite programming problem according to formula (1), refer to formula (2) as shown:

Among them, P ₀ sends the total power of the signal.

In this step S5, formula (2) is converted to obtain formula (3). Refer to the following:

Among them, ρ ₀ is the tracking target positioning error.

According to formula (4), construct the semi-definite programming problem of the minimum transmission power of the system, refer to formula (5):

The positioning and tracking system and method using wireless energy harvesting provided by the embodiments of the present application can continuously provide energy for the wireless IoT positioning system through the energy transmitting device 100 (E-AP), the passive anchor node 200 and the tracking target 300. The combination of microwave wireless charging technology and the wireless positioning system of the Internet of Things uses wireless charging technology to replace the traditional battery power supply, which solves the battery bottleneck problem. At the same time, in response to the specific needs of the positioning system, such as positioning accuracy and low energy consumption, the adopted power distribution method can adjust the signal power vector of the E-AP, and then control the accuracy of the system positioning and the overall power consumption to achieve power according to Need to be allocated to optimize the system.

The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also It should be regarded as the protection scope of the present invention.

Claims

A positioning and tracking system using wireless energy harvesting, characterized in that: the system includes an energy transmitting device, a passive anchor node and a tracking target;

The energy transmitting device sends a wireless energy signal to the passive anchor node;

The passive anchor node uses the received wireless energy signal as a power source to form a ranging signal and send it to the tracking target;

The tracking target is positioned according to the ranging signal, and the distance between it and the passive anchor node is obtained.
The positioning and tracking system using wireless energy harvesting according to claim 1, characterized in that: the energy transmitting device is set to include K antennas and form mutually orthogonal signal vectors x=[x 1 ,...,x K ] T , T means transposition; the power of each signal is
Where k refers to the k-th antenna, and the value of k is 1 to K, then the power vector of the signal r x =[r x 1 ,...,r x K ] T.
The positioning and tracking system using wireless energy harvesting according to claim 2, characterized in that there are N passive anchor nodes, and the channel matrix from the energy transmitting device to the passive anchor node is G=[g,... ,g N ] T , where each element g N =[G] kn represents the channel attenuation coefficient from the kth antenna to the nth passive anchor node, and the value of n is 1～N, then the channel attenuation coefficient vector Is g n =[g 1n ,…,g kn ]; get the defined channel gain
Is the mean square of g kn , the channel gain vector
The positioning and tracking system using wireless energy harvesting according to claim 3, characterized in that: the next Cramer is used as the measurement standard of the positioning accuracy of the system, wherein the next Cramer is the inverse matrix of the Fisher matrix; The power vector r x and the channel gain vector of the signal
Construct the Fisher matrix, specifically expressed as formula (1):

among them,
Is the direction angle matrix, φ is the direction angle at which the nth passive anchor node reaches the tracking target,
Background noise variance; d n is the distance between the target track passive anchor node, 2β is the attenuation factor of the signal propagation.
The positioning and tracking system using wireless energy harvesting according to claim 4, characterized in that: under the condition of a given signal power, a positive semi-definite programming problem is constructed according to formula (1) to improve the positioning accuracy of the system, and formula (2) is obtained :

Among them, P 0 is the total power of the transmitted signal.
The positioning tracking system using wireless energy harvesting according to claim 5, characterized in that: under a given positioning error requirement, formula (2) is described as follows to obtain the minimum transmission power of the system, and formula (3) is obtained:

Among them, ρ 0 is the positioning error of the tracking target.
The positioning and tracking system using wireless energy harvesting according to claim 4, characterized in that: the matrix inequality J e -1 ≤ Z is constructed, and the
Among them, I is the identity matrix, and Z is the matrix constructed, and then the semi-definite programming problem with the highest positioning accuracy is constructed, and formula (4) is obtained:

Among them, P 0 is the total power of the transmitted signal.
The positioning and tracking system using wireless energy harvesting according to claim 7, characterized in that the semi-definite programming problem of minimum transmission power is constructed according to formula (4), and formula (5) is obtained:
A method based on the positioning and tracking system using wireless energy harvesting according to claims 1-8, characterized in that the specific steps of the method are as follows:

Step S1: Set up a positioning and tracking system, including an energy transmitting device, passive anchor nodes and tracking targets. The energy transmitting device sends wireless energy signals to the passive anchor nodes for power supply; the passive anchor nodes form a ranging signal and send it to the tracking target ; The tracking target performs autonomous positioning according to the received ranging signal, and obtains the distance between it and the passive anchor node;

Step S2: Obtain the power vector r x of the signal sent by the energy transmitting device and the channel gain vector between the energy transmitting device and the passive anchor node

Step S3: According to the power vector r x of the signal and the channel gain vector
Construct a Fisher matrix, and use the inverse matrix of the Fisher matrix as the next term of Cramer, and use the next term of Cramer as the measurement standard of the positioning accuracy of the system;

Step S4: Under the condition of a given total power of the signal sent by the energy transmitting device, construct a positive semi-definite programming problem according to the Fisher matrix to improve the positioning accuracy of the system;

Step S5: Under the condition of a given tracking target positioning error requirement, the positive semi-definite programming problem is converted to obtain the minimum transmission power of the system.