CN105807254A - Mobile equipment's own information based wireless positioning method - Google Patents

Mobile equipment's own information based wireless positioning method Download PDF

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Publication number
CN105807254A
CN105807254A CN201610120483.8A CN201610120483A CN105807254A CN 105807254 A CN105807254 A CN 105807254A CN 201610120483 A CN201610120483 A CN 201610120483A CN 105807254 A CN105807254 A CN 105807254A
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mobile device
time
positioning
mobile equipment
mobile
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CN105807254B (en
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王田
王文华
陈永红
田晖
蔡奕侨
王成
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Huaqiao University
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Huaqiao University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0273—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves using multipath or indirect path propagation signals in position determination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses a mobile equipment's own information based wireless positioning method which takes already positioned mobile equipment as anchor points or a part of the anchor points for ranging and positioning to-be-positioned mobile equipment. In other words, the method uses already positioned mobile equipment as mobile anchor points to position other mobile equipment. As all positioned users can serve anchor points, the number of anchor points in an environment increases so that the problem of failing to position due to a limited number of anchor points can be addressed and consequently, the positioning rate of mobile equipment improves substantially. According to the invention, Kalman filtering is introduced and expanded in the method, which reduces the impacts of a multi-path effect and range finding errors, therefore, further increasing the positioning accuracy. The method of the invention can be performed with just general positioning nodes, requiring not so much on positioning hardware. In addition, the algorithmic calculating complexity remains low. Compared to a traditional positioning scheme, the method overcomes the deficiencies of requirements of stringent hardware for positioning nodes, complex algorithmic calculating, costly positioning and high calculating complexity.

Description

Wireless positioning method based on self information of mobile equipment
Technical Field
The invention relates to the technical field of wireless positioning, in particular to a wireless positioning method based on self information of mobile equipment.
Background
In recent years, wireless positioning technology has become more widely used in fields such as emergency rescue, mobile electronic commerce, military, industry, wireless sensors, and the like. In these areas, locating a user in motion is an important application. For example, safety accidents occur in hong Kong in the construction industry one fifth of the time each year. The safety management system can continuously monitor the positions of the moving workers and send out warning information when the workers approach a dangerous area, so that the occurrence of safety accidents is greatly reduced. This puts higher demands on the traditional positioning technology, on one hand, the mobile user can only be positioned by wireless, but the wireless positioning signal is unstable and is easily interfered by the environment, resulting in low positioning accuracy. On the other hand, in an indoor environment and the like, a traditional GPS signal cannot reach, and due to reasons such as obstruction, a global positioning system GPS has a great defect, and particularly in an indoor environment, the positioning rate and the positioning accuracy of the GPS for a mobile device are far from meeting the requirements of people. The signals of the fixed anchor points are also easily shielded by obstacles, so that the traditional positioning method is invalid.
Wireless positioning is mainly divided into two methods, ranging-based and non-ranging-based.
Because the positioning accuracy of the non-ranging-based method is low and cannot meet the requirement, the ranging-based positioning method becomes the key point of research of people.
The main process of the traditional positioning method based on ranging is to obtain the distance or angle information between the mobile equipment and an anchor point by measuring the information of signal arrival Time (TOA), signal arrival Time Difference (TDOA), signal arrival angle (AOA), signal strength indicator (RSSI) and the like from the mobile equipment to the fixed anchor point with known position, and then obtain the position information of the mobile equipment by positioning algorithms such as trilateration method, least square method and the like.
However, this method has the following disadvantages:
firstly, when fixed anchor points are few in the environment, the positioning of a user is difficult to realize, for example, a barrier blocks signals of the anchor points, and the mobile equipment cannot simultaneously acquire signals of more than 3 anchor points and cannot be positioned by using a traditional positioning method;
secondly, the positioning accuracy is low due to the influence of multipath effect, wireless signal interference and the like in the indoor environment. There are many drawbacks to conventional methods of locating a mobile device.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a wireless positioning method based on the self information of the mobile equipment, which has low cost, high positioning rate and high precision.
The technical scheme of the invention is as follows:
a wireless positioning method based on self information of mobile equipment takes the positioned mobile equipment as a whole anchor point or a part of anchor points to carry out ranging positioning on the mobile equipment to be positioned.
Preferably, the located mobile device broadcasts a signal carrying its ID and timestamp, the fixed anchor point or the mobile device receiving the signal calculates the distance to the located mobile device, and locates the mobile device according to the calculated distance information.
Preferably, when the mobile device to be positioned is positioned by the mobile device, the distance of the current time is obtained according to the timestamp in the information received by time, and then the positioning is performed.
Preferably, the method comprises the following specific steps:
1) initializing an initial position vector Pre _ X, an error covariance Pre _ p, process noise Q and measurement noise R of the mobile equipment;
2) calculating the distance D between the anchor point and the mobile device and between the mobile device and the mobile device according to the signal propagation timeij；
3) Predicting a state vector X _ P (t/t-1) at the time t according to the optimal state at the time t-1 and estimating a covariance P _ P (t/t-1);
4) calculating a predicted distance vector h _ Xp from the predicted state vector X _ p (t/t-1) at time t, and from the predicted distance vector h _ Xp and the actual measured value DijCalculating a measurement residual
5) Calculating a Kalman gain K (t) ═ P _ P (t/t-1) × (H) × P _ P (t/t-1) × HT)-1Wherein H is a parameter of the measurement system;
6) updating the optimal state X _ p (t/t-1) + K (t) Y _ e of the mobile device at the time t according to the predicted state vector X _ p (t/t-1) at the time t and the Kalman gain K (t);
7) updating the estimated covariance P _ P (t) (eye (length (X _ P)) ]p _ P (t/t-1);
8) and (5) repeating the steps 2) to 7) to carry out positioning at the t +1 moment.
Preferably, the state of a single mobile device at time t is represented as a state vector as follows:
x(t)＝[Lx(t)，Ly(t)，Vx(t)，Vy(t)]；
wherein Lx (t), Ly (t) respectively represent x-axis and y-axis coordinates of the mobile equipment, and Vx (t) and Vy (t) respectively represent the speed of the mobile equipment in the directions of the x axis and the y axis;
the state equations for the n mobile devices are then expressed as follows:
X(t)＝[x1(t)，x2(t)，…，xn(t)]T；
wherein x isi(T) represents the state vector of the ith mobile user, and T is the transpose operator.
Preferably, the mobile device predicts the state at time t by the following formula at time t-1:
X(t/t-1)＝FX(t-1)+W(t-1)；
wherein W (t-1) -N (0, Q) is process noise, and F represents a state transition matrix.
Preferably, the real state x (t) of the mobile device at time t is measured with a state vector z (t) that satisfies the following equation:
Z(t)＝f(X(t))+V(t)；
wherein, Δ T represents the time update interval, V (T) N (0, R) represents the measurement noise, and Z (T) represents the distance vector between the mobile device at time T and the fixed anchor point and any mobile device.
Preferably, the square of the distance is taken to constitute the measurement vector, then
Z ( t ) = [ D 11 2 ( t ) , ... , D i j 2 ( t ) , ... , D m n 2 ( t ) , D 12 2 ( t ) , ... , D j k 2 ( t ) , ... , D ( n - 1 ) n 2 ( t ) ] T ;
Wherein,representing the square of the distance between the anchor point i and the mobile device j (i-1, 2, …, m; j-1, 2, …, n), aixAnd AiyX-axis and y-axis coordinates representing the anchor point i, respectively (i ═ 1,2, …, m);
represents the square of the distance between mobile device j and mobile device k (j, k ≠ 1,2, …,4, and j ≠ k), Ljx(t) and Ljy(t) respectively represent the x-axis and y-axis coordinates of mobile device j at time t (j ═ 1,2, …, n).
The invention has the following beneficial effects:
the method of the invention uses the position information of the positioned mobile equipment to position other mobile equipment, namely the positioned mobile equipment is used as a 'mobile anchor point' to position other mobile equipment. Because the positioned users can serve as mobile anchor points, the number of the anchor points in the environment is greatly increased, the situations that positioning cannot be carried out due to the fact that the number of the fixed anchor points is too small are prevented, and the positioning rate of the mobile equipment is greatly improved. The invention introduces and expands Kalman filtering, reduces the influence of multipath effect, distance measurement error and the like in the environment and further improves the positioning precision.
The invention only needs general positioning nodes, has no excessive requirements on positioning hardware, and has lower calculation complexity of the algorithm. Compared with the traditional positioning scheme, the method overcomes the defects of high hardware requirement of the node, excessively complex positioning algorithm, increased positioning cost and calculation complexity and the like.
Drawings
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
In order to solve the defects of low positioning probability, poor positioning accuracy, complex positioning algorithm and the like in the prior art, the invention provides a wireless positioning method based on the self information of mobile equipment, which takes the positioned mobile equipment as all anchor points or part of anchor points to perform ranging positioning on the mobile equipment to be positioned.
In the invention, the mobile equipment to be positioned simultaneously utilizes the fixed anchor point and other positioned mobile equipment as reference nodes to position. Assuming that there are a few fixed anchor points with known positions and mobile devices with unknown positions in the environment area, the mobile devices and the fixed anchor points can communicate and measure the distances between them, and the mobile devices can also perform wireless communication and ranging, and can be implemented based on technical means such as TOA, RSSI, TDOA, and the like.
The specific process is as follows: the located mobile equipment broadcasts a signal carrying the ID and the timestamp of the mobile equipment, the fixed anchor point or the mobile equipment which receives the signal calculates the distance between the fixed anchor point or the mobile equipment and the located mobile equipment, and the mobile equipment is located according to the distance information obtained through calculation. And when the mobile equipment to be positioned is positioned through the mobile equipment, obtaining the distance of the current moment according to the timestamp in the information received by time, and then positioning.
As shown in FIG. 1, for a mobile device MS1And a mobile device MS3They can be respectively connected with fixed anchor points BS1,、BS2、BS3And a fixed anchor BS1、BS4、BS5Communicate, further according to formula di＝(ti-t0) C (i ═ 1,2, 3) determines the mobile device MS1And a mobile device MS3The distances between the fixed anchor points are obtained, and then the mobile equipment MS is obtained1And a mobile device MS3The position of (a). And for mobile device MS2It can only fix anchor point BS4Direct communication, it is difficult to locate it by conventional methods. In the invention, the positioned mobile equipment MS is utilized1And a mobile device MS3Acting as a mobile device MS2The mobile anchor point greatly increases the mobile equipment MS2The number of the referenceable anchor points is increased, and the positioning rate and the positioning precision are improved.
The invention improves the extended Kalman filtering to position the mobile equipment, and the state model and the measurement model are as follows:
the state of a single mobile device at time t is represented as a state vector as follows:
x(t)＝[Lx(t)，Ly(t)，Vx(t)，Vy(t)]；
wherein Lx (t), Ly (t) respectively represent x-axis and y-axis coordinates of the mobile equipment, and Vx (t) and Vy (t) respectively represent the speed of the mobile equipment in the directions of the x axis and the y axis;
the state equations for the n mobile devices are then expressed as follows:
X(t)＝[x1(t)，x2(t)，…，xn(t)]T；
wherein x isi(T) represents the state vector of the ith mobile user, and T is the transpose operator.
The mobile device predicts the state of the t moment by the following formula at the t-1 moment:
X(t/t-1)＝FX(t-1)+W(t-1)；
where W (t-1) -N (0, Q) are process noise, representing the uncertainty of the system and assumed to be Gaussian white noise, and F represents a state transition matrix that transitions the state from time t-1 to time t.
The true state x (t) of the mobile device at time t is measured and the state vector z (t) satisfies the following equation:
Z(t)＝f(X(t))+V(t)；
wherein, Δ T represents the time update interval, V (T) N (0, R) represents the measurement noise, again assumed to be white Gaussian noise, and Z (T) represents the distance vector between the mobile device at time T and the fixed anchor point and any mobile device.
In order to ensure that the measurement equation is a linear equation, in the invention, the square of the distance is taken to form a measurement vector, then
Z ( t ) = [ D 11 2 ( t ) , ... , D i j 2 ( t ) , ... , D m n 2 ( t ) , D 12 2 ( t ) , ... , D j k 2 ( t ) , ... , D ( n - 1 ) n 2 ( t ) ] T ;
Wherein,representing the square of the distance between the anchor point i and the mobile device j (i-1, 2, …, m; j-1, 2, …, n), aixAnd AiyX-axis and y-axis coordinates representing the anchor point i, respectively (i ═ 1,2, …, m);
represents the square of the distance between mobile device j and mobile device k (j, k ≠ 1,2, …,4, and j ≠ k), Ljx(t) and Ljy(t) respectively represent the x-axis and y-axis coordinates of mobile device j at time t (j ═ 1,2, …, n).
Based on the state model and the measurement model, the method specifically comprises the following steps:
1) initializing an initial position vector Pre _ X, an error covariance Pre _ p, process noise Q and measurement noise R of the mobile equipment;
2) calculating the distance D between the anchor point and the mobile device and between the mobile device and the mobile device according to the signal propagation timeij；
3) Predicting a state vector X _ P (t/t-1) at the time t by using a formula X (t/t-1) ═ FX (t-1) + W (t-1) and an optimal state at the time t-1, and estimating a covariance P _ P (t/t-1) ═ F _ P (t-1) × FT+ Q (t-1), where F is the state transition matrix and Q (t-1) is the estimation error at time t-1;
4) calculating a predicted distance vector h _ Xp from the predicted state vector X _ p (t/t-1) at time t, and from the predicted distance vector h _ Xp and the actual measured value DijCalculating a measurement residualI.e. the difference between the predicted and actual measured values;
5) calculating a Kalman gain K (t) ═ P _ P (t/t-1) × (H) × P _ P (t/t-1) × HT)-1Wherein H is a parameter of the measurement system;
6) updating the optimal state X _ p (t/t-1) + K (t) Y _ e of the mobile device at the time t according to the predicted state vector X _ p (t/t-1) at the time t and the Kalman gain K (t);
7) updating the estimated covariance P _ P (t) (eye (length (X _ P)) ]p _ P (t/t-1);
8) and (5) repeating the steps 2) to 7) to carry out positioning at the t +1 moment.
The above examples are provided only for illustrating the present invention and are not intended to limit the present invention. Changes, modifications, etc. to the above-described embodiments are intended to fall within the scope of the claims of the present invention as long as they are in accordance with the technical spirit of the present invention.

Claims (8)

1. A wireless positioning method based on self information of mobile equipment is characterized in that the positioned mobile equipment is used as a whole anchor point or a part of anchor points to carry out ranging positioning on the mobile equipment to be positioned.
2. The wireless positioning method based on the mobile device self information as claimed in claim 1, wherein the positioned mobile device broadcasts a signal carrying its own ID and timestamp, the fixed anchor point or the mobile device receiving the signal calculates the distance to the positioned mobile device, and positions the mobile device according to the calculated distance information.
3. The wireless positioning method based on the mobile device information as claimed in claim 2, wherein when the mobile device to be positioned is positioned by the mobile device, the distance of the current time is obtained according to the timestamp in the information received by time, and then the positioning is performed.
4. The wireless positioning method based on the self-information of the mobile device as claimed in claim 3, wherein the specific steps are as follows:
1) initializing an initial position vector Pre _ X, an error covariance Pre _ p, process noise Q and measurement noise R of the mobile equipment;
2) calculating the distance D between the anchor point and the mobile device and between the mobile device and the mobile device according to the signal propagation timeij；
3) Predicting a state vector X _ p (t/t-1) at the time t according to the optimal state at the time t-1, and estimating covariance p _ p (t/t-1);
4) calculating a predicted distance vector h _ Xp from the predicted state vector X _ p (t/t-1) at time t, and from the predicted distance vector h _ Xp and the actual measured value DijCalculating a measurement residual
5) Calculating a Kalman gain K (t) ═ P (t/t-1) × (H) × P-P (t/t-1) × HT)-1Wherein H is a parameter of the measurement system;
6) updating the optimal state X _ p (t/t-1) + K (t) Y _ e of the mobile device at the time t according to the predicted state vector X _ p (t/t-1) at the time t and the Kalman gain K (t);
7) updating the estimated covariance P _ P (t) (eye (length (X _ P)) ]p _ P (t/t-1);
8) and (5) repeating the steps 2) to 7) to carry out positioning at the t +1 moment.
5. The method of claim 4, wherein the state of a single mobile device at time t is represented as a state vector as follows:
x(t)＝[Lx(t)，Ly(t)，Vx(t)，Vy(t)]；
wherein Lx (t), Ly (t) respectively represent x-axis and y-axis coordinates of the mobile equipment, and Vx (t) and Vy (t) respectively represent the speed of the mobile equipment in the directions of the x axis and the y axis;
the state equations for the n mobile devices are then expressed as follows:
X(t)＝[x1(t),x2(t),...,xn(t)]T；
wherein x isi(T) represents the state vector of the ith mobile user, and T is the transpose operator.
6. The method of claim 5, wherein in step 3), the mobile device predicts the state of the mobile device at time t-1 according to the following formula:
X(t/t-1)＝FX(t-1)+W(t-1)；
wherein W (t-1) -N (0, Q) is process noise, and F represents a state transition matrix.
7. The method of claim 6, wherein the true state X (t) of the mobile device at time t is measured by the state vector Z (t) and satisfies the following equation:
z(t)＝f(X(t))+V(t)；
wherein, Δ T represents the time update interval, V (T) N (0, R) represents the measurement noise, and Z (T) represents the distance vector between the mobile device at time T and the fixed anchor point and any mobile device.
8. The wireless positioning method based on the mobile device self-information as claimed in claim 7, wherein the square of the distance is taken to form a measurement vector
Z ( t ) = [ D 11 2 ( t ) , ... , D i j 2 ( t ) , ... , D m n 2 ( t ) , D 12 2 ( t ) , ... , D j k 2 ( t ) , ... , D ( n - 1 ) n 2 ( t ) ] T ;
Wherein,representing the square of the distance between the anchor point i and the mobile device j (i-1, 2, …, m; j-1, 2, …, n), aixAnd AiyX-axis and y-axis coordinates representing the anchor point i, respectively (i ═ 1,2, …, m);
represents the square of the distance between mobile device j and mobile device k (j, k ≠ 1,2, …,4, and j ≠ k), Ljx(t) and Ljy(t) respectively represent the x-axis and y-axis coordinates of mobile device j at time t (j ═ 1,2, …, n).
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Cited By (4)

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CN106413085A (en) * 2016-09-09 2017-02-15 华侨大学 Mobile anchor localization method based on distributed election
CN109188351A (en) * 2018-08-16 2019-01-11 佛山科学技术学院 A kind of wirelessly anti-interference localization method and device
CN110493740A (en) * 2018-05-14 2019-11-22 中国移动通信有限公司研究院 A kind of indoor orientation method and location-server
CN113891245A (en) * 2021-11-17 2022-01-04 西安邮电大学 Fire scene fireman cooperative relay positioning method

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CN101873692A (en) * 2010-06-23 2010-10-27 电子科技大学 Wireless sensor network node positioning method based on time reversal
CN102088769A (en) * 2010-12-23 2011-06-08 南京师范大学 Wireless location method for directly estimating and eliminating non-line-of-sight (NLOS) error
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EP1834500B1 (en) * 2005-01-03 2008-05-14 France Télécom Method of measuring a distance between two radio-communication devices and device adapted to implement one such method
CN101819267A (en) * 2010-04-02 2010-09-01 上海交通大学 Target tracking method based on receipt signal energy indication measurement
CN101873692A (en) * 2010-06-23 2010-10-27 电子科技大学 Wireless sensor network node positioning method based on time reversal
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106413085A (en) * 2016-09-09 2017-02-15 华侨大学 Mobile anchor localization method based on distributed election
CN110493740A (en) * 2018-05-14 2019-11-22 中国移动通信有限公司研究院 A kind of indoor orientation method and location-server
CN110493740B (en) * 2018-05-14 2021-01-15 中国移动通信有限公司研究院 Indoor positioning method and positioning server
CN109188351A (en) * 2018-08-16 2019-01-11 佛山科学技术学院 A kind of wirelessly anti-interference localization method and device
CN113891245A (en) * 2021-11-17 2022-01-04 西安邮电大学 Fire scene fireman cooperative relay positioning method
CN113891245B (en) * 2021-11-17 2024-04-26 西安邮电大学 Fire scene firefighter cooperative relay positioning method

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