CN106612543B

CN106612543B - Indoor positioning self-adaptive sampling method and device

Info

Publication number: CN106612543B
Application number: CN201510694564.4A
Authority: CN
Inventors: 吴彤; 肖登坤; 熊艳伟
Original assignee: Beijing Jinkun Innovation Technology Co ltd
Current assignee: Beijing Jinkun Innovation Technology Co ltd
Priority date: 2015-10-22
Filing date: 2015-10-22
Publication date: 2020-06-09
Anticipated expiration: 2035-10-22
Also published as: CN106612543A

Abstract

The invention provides an indoor positioning self-adaptive sampling method, which is characterized by comprising the following steps: and configuring a periodically triggered self-adaptive database updating period, a sampling sending interval and an event triggered characteristic quantity difference threshold value of self-adaptive database updating through a network side. When the system detects that the database meets the condition of periodic update or event update, a sampling instruction is sent to the sampling terminal through the network side so as to instruct the sampling terminal to send wireless signals according to the configuration of the network side, and meanwhile, the network side extracts the characteristic quantity of the wireless signals of the sampling terminal and dynamically updates the current database. The method can lead the system to adaptively match the dynamic change of the wireless environment, and improve the indoor positioning precision of the system.

Description

Indoor positioning self-adaptive sampling method and device

Technical Field

The invention belongs to the field of indoor positioning and short-distance communication.

Background

The indoor positioning means that position positioning is realized in an indoor environment, and a set of indoor position positioning system is formed by mainly integrating multiple technologies such as wireless communication, base station positioning, inertial navigation positioning and the like, so that position monitoring of personnel, objects and the like in an indoor space is realized. Besides cellular positioning technologies of communication networks, common indoor wireless positioning technologies include: Wi-Fi, Bluetooth, Infrared, ultra Wide band, RFID, ZigBee, and ultrasound.

The fingerprint matching (RFPM) method is an important means in indoor and outdoor positioning, and particularly in indoor positioning, the method has a wide application range, such as mall positioning, exhibition positioning, office building positioning, airport positioning, tunnel positioning, mine positioning, and the like. The wireless signal characteristic vector is collected on each grid by rasterizing a wireless area to be observed and monitored to build a database which can be used for signal characteristic matching and used for subsequent positioning position coordinate calculation. However, the existing scheme has low applicability in a complex and variable wireless environment, and an indoor positioning method with small engineering deployment amount, wide applicability to the wireless environment and high positioning accuracy needs to be provided urgently.

Disclosure of Invention

The invention aims to provide an adaptive sampling method and an adaptive sampling device for indoor positioning, which adapt to the change of a wireless environment.

In order to achieve the above object, the content of the present invention includes the following three parts:

process of adaptive dynamic sampling algorithm

Step 1: in an actual environment, N sampling devices are deployed at equal intervals or unequal intervals according to a certain distance.

Step 2: the system is configured with a sampling database updating period of a periodic trigger mode, a wireless signal transmission interval of a sampling device, a sampling database updating threshold of an event trigger mode and a hysteresis value set by the system.

And step 3: and finishing initial system off-line sampling, and building an initial database for positioning fingerprint matching.

And 4, step 4: is it determined whether an adaptive update cycle node of a periodic trigger mode has been reached? If yes, executing step 5; if not, go to step 7.

And 5: and the system issues a dynamic sampling instruction.

Step 6: and (3) the self-adaptive sampling device receives the sampling instruction, transmits the wireless signal according to the instruction configuration so as to complete the new characteristic sampling of the primary wireless environment by matching with the system, dynamically updates the fingerprint matching database and skips to the step 9.

And 7: judging whether the difference between each signal characteristic extraction value in the sampling base and each current channel characteristic extraction value is larger than the threshold value of the event triggering method, if so, executing the step 8; if not, jumping to step 5.

And 8: the existing fingerprint matching database is maintained unchanged.

And step 9: and the network side issues a power saving state instruction and monitors whether the next database updating condition is met.

Step 10: the algorithm ends.

Two, self-adaptive dynamic sampling device

The self-adaptive dynamic sampling device is composed of a microprocessor, a wireless transmitting module, a wireless receiving module and a power supply module. The microprocessor is mainly used for decoding the self-adaptive dynamic sampling instruction received by the wireless receiving module and controlling the wireless sending module to send wireless signals at corresponding intervals according to the configuration parameters; the wireless sending module sends wireless signals to the outside; the wireless receiving module is used for receiving a control instruction from a network side (positioning base station); and the power supply module supplies power to the whole self-adaptive dynamic sampling device.

Three, self-adaptive dynamic sampling system

The self-adaptive dynamic sampling system consists of a self-adaptive sampling device, a positioning base station and a positioning engine.

The self-adaptive sampling device is a terminal device which is matched with self-adaptive dynamic sampling.

The positioning base station is a transmission pipeline of the whole system and is responsible for issuing dynamic sampling instructions, extracting characteristic quantities (such as wireless signal strength indication, RSSI, ID of the self-adaptive sampling device, timestamp and the like) of wireless signals of the self-adaptive sampling device after the wireless signals are scanned, and sending the characteristic quantities to a positioning engine.

The positioning engine has the function of executing the positioning algorithm of the system, wherein the positioning engine comprises the self-adaptive sampling method, and the self-adaptive sampling updating configuration of periodic triggering and event triggering is configured, judged, executed and issued with instructions in the positioning engine. Meanwhile, the positioning engine is an entity for finally calculating the position coordinates of the object to be measured.

The invention has the beneficial effects that:

the indoor positioning self-adaptive sampling method and the indoor positioning self-adaptive sampling device can be effectively applied to scenes with large wireless environment change, such as wireless environments of mines, tunnels, markets and the like.

The self-adaptive dynamic sampling device is convenient and reliable in practical engineering application and low in engineering complexity.

The core method of the invention is based on the configurable period and the periodic and event mixed triggering mode of the configurable threshold, and can well take the power saving performance of the sampling device and the real-time performance of adapting to the change of the wireless environment into account.

Drawings

FIG. 1 is a flow chart of an adaptive dynamic sampling algorithm

FIG. 2 is a block diagram of an adaptive dynamic sampling device module architecture

FIG. 3 is a block diagram of an adaptive dynamic sampling system

FIG. 4 is a schematic view of the environment configuration of embodiment 1

FIG. 5 is a schematic view of the environment configuration of example 2

FIG. 6 is an environmental configuration diagram of example 3

Detailed Description

Example 1:

as shown in fig. 4, it is assumed that positioning base stations are deployed at a station spacing of 50m in the system, a WLAN technology adopted by the positioning base stations is WIFI, and sampling terminals integrated with WIFI chips are deployed at equal intervals of 5 m. The key parameter configuration of the system is as follows:

parameter name	Parameter value
		Adaptive database update cycle	12 hours (h)
Sample transmission interval	500 milliseconds (ms)
		Feature amount difference threshold value	6dB

Example 2:

as shown in fig. 5, it is assumed that a positioning base station is deployed in a system according to a station distance of 80m, a WLAN technology adopted by the positioning base station is Zigbee, and sampling terminals integrated with Zigbee chips are deployed at unequal intervals and are only placed at a place where high-precision positioning is required. The key parameter configuration of the system is as follows:

parameter name	Parameter value
		Adaptive dataBank update period	12 hours (h)
Sample transmission interval	500 milliseconds (ms)
		Feature amount difference threshold value	6dB

Example 3:

as shown in fig. 6, it is assumed that a positioning base station is deployed at a station spacing of 15m in the system, a WLAN technology adopted by the positioning base station is Bluetooth (Bluetooth), and sampling terminals integrated with Bluetooth chips are deployed at an equal interval of 3 m. The key parameter configuration of the system is as follows:

parameter name	Parameter value
		Adaptive database update cycle	24 hours (h)
Sample transmission interval	400 milliseconds (ms)
		Feature amount difference threshold value	6dB

Claims

1. An indoor positioning self-adaptive sampling method is characterized in that:

configuring a periodically triggered self-adaptive database updating period and a sampling sending interval through a network side;

configuring a feature quantity difference threshold value of adaptive database updating triggered by an event through a network side;

when the system reaches the update cycle time point of the self-adaptive database, the network side sends a sampling instruction to the sampling terminal; or, when the system monitors that the difference between the characteristic quantity of the current wireless environment and the characteristic quantity in the database exceeds the characteristic quantity difference threshold value configured on the network side and the hysteresis value set by the system, the network side sends a sampling instruction to the sampling terminal;

after receiving a sampling instruction of a network side, a sampling terminal sends a wireless signal to the outside according to a sampling sending interval configured by the network side;

the network side receives the wireless signal from the sampling terminal, extracts the corresponding wireless environment characteristic quantity and updates the current database;

and after the system finishes updating the database, the network side sends a power-saving state indication to the sampling terminal, and the sampling terminal restores to the power-saving state.

2. The indoor positioning adaptive sampling method of claim 1, wherein:

the numerical value of the updating period can reflect the change period of the wireless environment, the time granularity of the updating period is longer, and the time unit can be selected from seconds, minutes, hours and days.

3. The indoor positioning adaptive sampling method of claim 1, wherein:

the sampling sending interval is a time interval configured by a network side and used for sending a wireless signal to the network side by a sampling terminal, the interval comprehensively considers the convenience of extracting the characteristic quantity of the wireless signal and the power consumption of the sampling terminal, and the time granularity of the interval can be selected from microseconds (us), milliseconds (ms) and seconds.

4. The indoor positioning adaptive sampling method of claim 1, wherein:

the characteristic quantity refers to characteristic parameters of the wireless signal, including but not limited to: received Signal Strength Indicator (RSSI), time of arrival (TOA), angle of arrival (AOA), Received Signal Strength Difference (RSSD), time difference of arrival (TDOA), angle of arrival (ADOA).

5. The indoor positioning adaptive sampling method of claim 1, wherein:

the characteristic quantity difference threshold is used for judging whether the change of the characteristic quantity exceeds a threshold set by a system, namely whether the change of the wireless environment exceeds the acceptable range of the system;

the hysteresis value set by the system is used for avoiding the ping-pong effect caused by misjudgment due to the fluctuation of wireless signals, and the robustness of the system algorithm can be enhanced by setting the hysteresis value;

if the system monitors that the difference between the characteristic quantity of the current wireless environment and the characteristic quantity in the system database exceeds the characteristic quantity difference threshold value configured on the network side, the system indicates that the current system database is not suitable for the current wireless environment, and the dynamic database needs to be updated.

6. The indoor positioning adaptive sampling method of claim 1, wherein:

the sampling terminal is composed of a micro processing unit (MCU), a wireless transmitting module, a wireless receiving module and a power supply module.

7. The indoor positioning adaptive sampling method of claim 6, wherein:

the micro processing unit (MCU) is used for receiving and processing various instructions from the network side, including but not limited to a sampling instruction and a power saving state instruction; decoding a sampling sending interval configured to a sampling terminal by a network side or decoding a power saving state instruction configured by the network side, and executing specified operation according to the instruction content;

the wireless transmitting module transmits a wireless signal to an external environment according to the instruction of a micro processing unit (MCU);

the wireless receiving module can keep monitoring the signals of the network side, and once receiving the instruction signals from the network side, the wireless receiving module can convert the received wireless instruction signals into electric signals and transmit the electric signals to a micro processing unit (MCU);

and the power supply module supplies power to the whole sampling terminal.

8. The indoor positioning adaptive sampling method of claim 1, wherein:

the self-adaptive database is used for storing all characteristic quantities in a wireless environment and plays a role in data fingerprint matching when a system needs to position a target to be detected and solve position coordinates;

the self-adaptive database obtains initial database information through offline sampling of the system at the initial stage of system operation and is packaged in the system; when the condition that the database needs to be updated is met along with the change of the wireless environment, the system adaptively updates the database.

9. The indoor positioning adaptive sampling method of claim 1, wherein:

the power saving state is that the sampling terminal is in a silent state for a long time to achieve the effect of power saving, and only in a default, fixed and relatively long time period, a wireless signal is sent to the outside once to be used for the system network side to judge the validity of the current database.