CN101191833A - A radio frequency identification indoor positioning detection method based on received signal strength - Google Patents

Abstract

Translated fromChinese

本发明公开了一种基于接收信号强度的射频识别室内定位检测方法，具体思想是：对于每一个待定位标签和参考标签，分别定义其信号强度向量S_i和θ_i，对于n个读卡器和m个参考标签，引入欧几里德距离度量获得某个待定位标签的欧式距离向量，然后依据某个待定位标签与离它位置最近的参考标签所计算得到的距离度量值将最小。通过这个方法，可以获得待定位标签的若干个近邻标签，并通过它们已知的位置坐标来对待定位标签的位置进行推断。本发明提供了一种有效的二维定位算法，实现了依据室内的已知位置参考标签对移动标签的定位。

The invention discloses a radio frequency identification indoor positioning detection method based on received signal strength. The specific idea is: for each tag to be positioned and a reference tag, respectively define its signal strength vector S_i and θ_i , for n card readers and m reference tags, introduce the Euclidean distance metric to obtain the Euclidean distance vector of a tag to be located, and then the distance metric calculated based on a tag to be located and the reference tag closest to its position will be the smallest. Through this method, several neighboring tags of the tag to be located can be obtained, and the position of the tag to be located can be inferred through their known position coordinates. The invention provides an effective two-dimensional positioning algorithm, and realizes the positioning of the mobile label based on the known position reference label in the room.

Description

Translated fromChinese

一种基于接收信号强度的射频识别室内定位检测方法A radio frequency identification indoor positioning detection method based on received signal strength

技术领域technical field

本发明涉及一种适用于室内无线定位技术的基于接收信号强度(RSS)的(RFID)室内定位检测方法。The invention relates to a (RFID) indoor positioning detection method based on received signal strength (RSS), which is suitable for indoor wireless positioning technology.

背景技术Background technique

RFID(射频识别)是一种非接触的自动识别技术，其基本原理是利用射频信号和空间耦合(电感耦合或电磁耦合)传输特性，实现对被识别物体的自动识别，具有许多传统的自动识别技术无可比拟的优点，如非接触、距离远、可读写、信息量大、无须人工干预、多目标同时识别等。RFID (Radio Frequency Identification) is a non-contact automatic identification technology. Its basic principle is to use the transmission characteristics of radio frequency signals and space coupling (inductive coupling or electromagnetic coupling) to realize automatic identification of identified objects. It has many traditional automatic identification methods. The unparalleled advantages of technology, such as non-contact, long distance, readable and writable, large amount of information, no manual intervention, multi-target simultaneous recognition, etc.

RSS参数，即RFID读卡器阅读标签时所接收到的无线信号强度，通常用watt或者dBm来进行度量，是一个和距离相关的通信参数，且目前市场上的主流RFID读写器都开始逐渐支持直接输出RSS强度的功能，较之其它通信参数而言更加容易获得。The RSS parameter, that is, the wireless signal strength received by the RFID card reader when reading the tag, usually measured in watt or dBm, is a communication parameter related to distance, and the mainstream RFID readers on the market are beginning to gradually Supports the function of directly outputting RSS intensity, which is easier to obtain than other communication parameters.

发明内容Contents of the invention

本发明的目的是提出一种基于接收信号强度的射频识别室内定位检测方法，该定位检测方法利用了RSS参数易收集并且与距离有良好相关性的特点，收集各标签的RSS参数进行分析处理，根据接收信号强度(RSS)的判断准则，寻找到若干个与待定位标签最为相似的参考标签，并根据待定位标签和这些参考标签的数值关系对待定位标签进行定位。充分考虑到了RFID室内传播机理和信道衰落的统计特性以及能量损耗的经验模型，能够有效地对室内RFID读卡器阅读标签进行定位。The purpose of the present invention is to propose a radio frequency identification indoor positioning detection method based on received signal strength. This positioning detection method utilizes the characteristics that RSS parameters are easy to collect and have good correlation with distance, and collect the RSS parameters of each tag for analysis and processing. According to the judgment criterion of received signal strength (RSS), several reference tags that are most similar to the tags to be located are found, and the tags to be located are located according to the numerical relationship between the tags to be located and these reference tags. Taking full account of the RFID indoor propagation mechanism and the statistical characteristics of channel fading and the empirical model of energy loss, it can effectively locate the tags read by indoor RFID readers.

本发明是基于RSS的RFID室内定位检测方法，利用了RSS参数易收集并且与距离有良好相关性的特点，收集各标签的RSS参数进行分析处理，根据本算法设计的判断准则，寻找到若干个与待定位标签最为相似的参考标签，并根据待定位标签和这些参考标签的数值关系对待定位标签进行定位。The present invention is an RSS-based RFID indoor positioning detection method, utilizes the characteristics that RSS parameters are easy to collect and has good correlation with distance, collects the RSS parameters of each tag for analysis and processing, and finds several The reference tags most similar to the tags to be positioned are selected, and the tags to be positioned are positioned according to the numerical relationship between the tags to be positioned and these reference tags.

本发明基于接收信号强度的射频识别室内定位检测方法的优点在于：(1)使用RFID技术，可以实现非接触的远距离读写；(2)利用RSS参数，更易于收集相关信息；(3)使用了基于RSS强度的近邻搜索法NNSS(Nearest Neighbors basedon Signal Strength)，能够简便有效的对收集的信息进行处理和匹配，选出适合的参考标签；(4)本发明中为室内定位检测建立了普适性信号空间，提高了算法的普适性。The advantages of the radio frequency identification indoor positioning detection method based on received signal strength of the present invention are: (1) using RFID technology, non-contact long-distance reading and writing can be realized; (2) using RSS parameters, it is easier to collect relevant information; (3) Using the nearest neighbor search method NNSS (Nearest Neighbors based on Signal Strength) based on RSS strength, the collected information can be easily and effectively processed and matched, and a suitable reference tag can be selected; (4) In the present invention, an indoor positioning detection is established The universal signal space improves the universality of the algorithm.

附图说明Description of drawings

图1是本发明在室内环境中安放四台读卡器的布局结构示意图。FIG. 1 is a schematic diagram of the layout of four card readers in an indoor environment according to the present invention.

图2是本发明定位检测处理的流程图。Fig. 2 is a flow chart of positioning detection processing in the present invention.

图3是本发明定位检测处理的另一流程图。Fig. 3 is another flow chart of the positioning detection processing of the present invention.

具体实施方式Detailed ways

下面将结合附图和实施例对本发明做进一步的详细说明。The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

本发明对待定位标签的位置估计是构建于近邻搜索的理论基础之上，具体思想是：对于每一个待定位标签和参考标签，分别定义信号强度向量，并引入欧几里德距离(欧氏距离)度量，对参考标签和待定位标签之间的位置关系进行判断，从而对未知标签进行定位。通过这个方法，可以获得待定位标签的若干个近邻标签，并通过它们已知的位置坐标来对待定位标签的位置进行推断。本发明提供了一种有效的二维定位算法，实现了依据室内的已知位置参考标签对移动标签的定位。针对本发明定位检测方法的处理步骤参见图2所示的流程。The position estimation of the tag to be positioned in the present invention is based on the theoretical basis of neighbor search, and the specific idea is: for each tag to be positioned and the reference tag, respectively define signal strength vectors, and introduce Euclidean distance (Euclidean distance ) measurement, to judge the positional relationship between the reference label and the label to be located, so as to locate the unknown label. Through this method, several neighboring tags of the tag to be located can be obtained, and the position of the tag to be located can be inferred through their known position coordinates. The invention provides an effective two-dimensional positioning algorithm, and realizes the positioning of the mobile label based on the known position reference label in the room. For the processing steps of the positioning detection method of the present invention, refer to the flow chart shown in FIG. 2 .

本发明基于接收信号强度(RSS)的射频识别(RFID)室内定位检测方法包括以下的几个步骤：The radio frequency identification (RFID) indoor positioning detection method based on received signal strength (RSS) of the present invention comprises following several steps:

第一步：先由n个读卡器分别对第b个参考标签进行采集其接收信号强度值

且$\stackrel{\→}{{\mathrm{\θ}}_b}=\{{\mathrm{\θ}}_1,{\mathrm{\θ}}_2,{\mathrm{\θ}}_3{\·\·\·\·\·\·\mathrm{\θ}}_n\};$Step 1: Firstly, n card readers collect the received signal strength value of the b-th reference tag respectively

and$\stackrel{\&Right\; Arrow;}{{\mathrm{\θ}}_b}=\{{\mathrm{\θ}}_1,{\mathrm{\θ}}_2,{\mathrm{\θ}}_3{\&Center\; Dot;\&Center\; Dot;\·\·\&Center\; Dot;\&Center\; Dot;\mathrm{\θ}}_{\mathrm{no}}\};$

θ₁表示第1个读卡器对第b个参考标签采集的接收信号强度值，θ₁ represents the received signal strength value collected by the first card reader for the b-th reference tag,

θ₂表示第2个读卡器对第b个参考标签采集的接收信号强度值，θ₂ represents the received signal strength value collected by the second card reader for the b-th reference tag,

θ₃表示第3个读卡器对第b个参考标签采集的接收信号强度值，θ₃ represents the received signal strength value collected by the third card reader for the b reference tag,

θ_n表示第n个读卡器对第b个参考标签采集的接收信号强度值。θ_n represents the received signal strength value collected by the nth card reader for the bth reference tag.

然后由n个读卡器分别对第a个待定位标签进行采集其接收信号强度值且Then the n card readers respectively collect the received signal strength value of the ath tag to be located and

$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>a</span>a</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span>{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>n</span>no</span>}}<span><span>\}</span>\}</span><span><span>;</span>;</span>$

S₁表示第1个读卡器对第a个待定位标签采集的接收信号强度值，S₁ represents the received signal strength value collected by the first card reader for the a-th tag to be located,

S₂表示第2个读卡器对第a个待定位标签采集的接收信号强度值，S₂ represents the received signal strength value collected by the second card reader for the a-th tag to be located,

S₃表示第3个读卡器对第a个待定位标签采集的接收信号强度值，S₃ represents the received signal strength value collected by the third card reader for the a-th tag to be located,

S_n表示第n个读卡器对第a个待定位标签采集的接收信号强度值。S_n represents the received signal strength value collected by the nth card reader for the ath tag to be located.

然后将参考标签强度待定位标签强度

传送给数据采集器；Then refer to the label strength Label strength to be located

sent to the data collector;

第二步：数据采集器对接收的参考标签强度待定位标签强度

依据欧几里德距离度量$E_{a,b}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}$获得第a个待定位标签的欧式距离向量；Step 2: The data collector receives the reference tag strength Label strength to be located

According to the Euclidean distance metric${\mathrm{E.}}_{a,b}={\left(\underset{i=1}{\overset{\mathrm{no}}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}$ Obtain the Euclidean distance vector of the a-th tag to be located;

i表示第i个读卡器，θ_i表示第i个读卡器上读出的参考标签接收信号强度值，S_i表示第i个读卡器上读出的待定位标签接收信号强度值；i represents the i-th card reader, θ_i represents the received signal strength value of the reference tag read on the i-th card reader, S_i represents the received signal strength value of the tag to be positioned read on the i-th card reader;

第三步：重复第二步获得所有m个参考标签与第a个待定位标签的欧几里德距离度量E_a，j，且j∈(1，m)，j表示第j个参考标签；The third step: Repeat the second step to obtain the Euclidean distance measure E_a,j between all m reference tags and the a-th tag to be located, and j∈(1,m), j represents the j-th reference tag;

第四步：对第三步获得的第1个参考标签与第a个待定位标签的距离度量E_a，1、第2个参考标签与第a个待定位标签的距离度量E_a，2、第3个参考标签与第a个待定位标签的距离度量E_a，3……第m个参考标签与第a个待定位标签的距离度量E_a，m进行从小到大排序；The fourth step: the distance measure E a, 1 between the first reference tag and the a-th tag to be located obtained in the third step_{, the distance measure E a} , 2 between the second reference tag and the a-th tag to be located_, The distance measure E_{a, 3} between the 3rd reference tag and the a-th tag to be located ... The distance measure E_{a, m} between the m-th reference tag and the a-th tag to be located is sorted from small to large;

第五步：选出第四步中最小的四个距离度量所对应的四个参考标签；所述四个参考标签即为距第a个待定位标签最近的四个近邻标签；The fifth step: select the four reference tags corresponding to the smallest four distance measures in the fourth step; the four reference tags are the four nearest neighbor tags from the ath tag to be located;

第六步：依据这四个近邻标签已知的位置坐标，计算出第a个待定位标签的估计位置。当某个参考标签相距第a个待定位标签的距离度量越小时则认为此参考标签与第a个待定位标签越近。Step 6: Based on the known position coordinates of the four neighboring tags, calculate the estimated position of the a-th tag to be located. When the distance measure between a reference tag and the a-th tag to be located is smaller, it is considered that the reference tag is closer to the a-th tag to be located.

针对如图1所示的其余待定位标签，重复上述步骤可获得每一个待定位标签的估计位置。For the rest of the tags to be positioned as shown in FIG. 1 , the above steps can be repeated to obtain the estimated position of each tag to be positioned.

为了减小本发明定位检测的误差，保证对待定位标签的位置精确定位，也可在上述第一步结束后，第二步开始前进行普适性信号空间模型的处理，即基于接收信号强度(RSS)的射频识别(RFID)室内定位检测方法包括以下的几个步骤：In order to reduce the error of the positioning detection of the present invention and ensure the precise positioning of the position of the label to be positioned, it is also possible to perform the processing of the universal signal space model after the above-mentioned first step ends and before the second step starts, that is, based on the received signal strength ( The radio frequency identification (RFID) indoor positioning detection method of RSS) comprises the following several steps:

第一步：先由n个读卡器分别对第b个参考标签进行采集其接收信号强度值

且$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_b}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3{\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\mathrm{\&theta;}}_n\};$Step 1: Firstly, n card readers collect the received signal strength value of the b-th reference tag respectively

and$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_b}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3{\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&CenterDot;\&Center\; Dot;\mathrm{\&theta;}}_{\mathrm{no}}\};$

然后由n个读卡器分别对第a个待定位标签进行采集其接收信号强度值

且Then the n card readers respectively collect the received signal strength value of the ath tag to be located

and

$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>a</span>a</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span>{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>n</span>no</span>}}<span><span>\}</span>\}</span><span><span>;</span>;</span>$

然后将参考标签强度

待定位标签强度

传送给数据采集器；Then refer to the label strength

Label strength to be located

sent to the data collector;

对于数据采集器中的信息量进行普适性信号空间模型处理后再进行第二步：数据采集器对接收的参考标签强度

待定位标签强度

依据欧几里德距离度量$E_{a,b}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}$获得第a个待定位标签的欧式距离向量；For the amount of information in the data collector, process the universal signal space model before proceeding to the second step: the data collector evaluates the strength of the received reference tag

Label strength to be located

According to the Euclidean distance metric${\mathrm{E.}}_{a,b}={\left(\underset{i=1}{\overset{\mathrm{no}}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}$ Obtain the Euclidean distance vector of the a-th tag to be located;

第三步：重复第二步获得所有m个参考标签与第a个待定位标签的欧几里德距离度量E_a，j，且j∈(1，m)，j表示第j个参考标签；The third step: Repeat the second step to obtain the Euclidean distance measure E_a,j between all m reference tags and the a-th tag to be located, and j∈(1,m), j represents the j-th reference tag;

第四步：对第三步获得的第1个参考标签与第a个待定位标签的距离度量E_a，1、第2个参考标签与第a个待定位标签的距离度量E_a，2、第3个参考标签与第a个待定位标签的距离度量E_a，3……第m个参考标签与第a个待定位标签的距离度量E_a，m进行从小到大排序；The fourth step: the distance measure E a, 1 between the first reference tag and the a-th tag to be located obtained in the third step_{, the distance measure E a} , 2 between the second reference tag and the a-th tag_{to be located,} The distance measure E_{a, 3} between the 3rd reference tag and the a-th tag to be located ... The distance measure E_{a, m} between the m-th reference tag and the a-th tag to be located is sorted from small to large;

第五步：选出第四步中最小的四个距离度量所对应的四个参考标签；所述四个参考标签即为距第a个待定位标签最近的四个近邻标签；The fifth step: select the four reference tags corresponding to the smallest four distance measures in the fourth step; the four reference tags are the four nearest neighbor tags from the ath tag to be located;

第六步：依据这四个近邻标签已知的位置坐标，计算出第a个待定位标签的估计位置。当某个参考标签相距第a个待定位标签的距离度量越小时则认为此参考标签与第a个待定位标签越近。Step 6: Based on the known position coordinates of the four neighboring tags, calculate the estimated position of the a-th tag to be located. When the distance measure between a reference tag and the a-th tag to be located is smaller, it is considered that the reference tag is closer to the a-th tag to be located.

普适性信号空间模型的构建使用了一种估计信号强度增量Δrss的方法来对原信号空间进行修正，基本思想就是以待定位标签作为标准标签，对定位场景中所有参考标签的信号空间分别进行估计修正，然后再将修正后的信号空间用于后续定位，即对每个参考标签而言，将其信号空间中的每一项减去修正参数rssm，使得由估计信号强度增量Δrss带来的误差减到最小。The construction of the universal signal space model uses a method of estimating the signal strength increment Δrss to correct the original signal space. Carry out estimation correction, and then use the corrected signal space for subsequent positioning, that is, for each reference tag, subtract the correction parameter rssm from each item in its signal space, so that the estimated signal strength increment Δrss with The resulting error is minimized.

普适性信号空间模型为：The universal signal space model is:

//n：系统中读卡器的数量//n: the number of card readers in the system

//REFTAGNUM：系统中参与定位的参考标签的数量//REFTAGNUM: The number of reference tags involved in positioning in the system

//rssm：修正参数//rssm: modify parameters

//TAG_TRACK_RSS：待定位标签的信号空间//TAG_TRACK_RSS: the signal space of the tag to be positioned

//TAG_REF_RSS(:，i)：第i个参考标签的信号空间//TAG_REF_RSS(:, i): the signal space of the i-th reference tag

//sum(T)：对信号空间向量T个元素求和//sum(T): Sum the T elements of the signal space vector

for(i＝1：REFTAGNUM)for (i=1:REFTAGNUM)

    rssm＝(sum(TAG_TRACK_RSS)-sum(TAG_REF_RSS(:，i)))/n；rssm=(sum(TAG_TRACK_RSS)-sum(TAG_REF_RSS(:,i)))/n;

    TAG_REF_RSS(:，i)＝TAG_REF_RSS(:，i)+rssm；TAG_REF_RSS(:, i) = TAG_REF_RSS(:, i)+rssm;

Endend

经过修正参数rssm修正后的信号空间称为普适性信号空间，普适性信号空间的建立使标签间差异造成的信号空间失真降到了最小，为近邻搜索过程提供了统一的距离度量计算平台，提高了基于RSS的RFID近邻定位算法的普适性，使其能够应对实际应用中多标签共存的状况。The signal space corrected by the correction parameter rssm is called the universal signal space. The establishment of the universal signal space minimizes the signal space distortion caused by the difference between labels, and provides a unified distance measurement calculation platform for the neighbor search process. The universality of the RSS-based RFID neighbor positioning algorithm is improved, so that it can cope with the coexistence of multiple tags in practical applications.

实施例1：针对49个参考标签与7个待定位标签的位置估计Example 1: Position estimation for 49 reference tags and 7 tags to be located

参见图1所示，在室内环境中的四个角上安放四台读卡器(A读卡器、B读卡器、C读卡器、D读卡器)，尽量均匀分布在四周，在环境空间中以1m的等间隔的放置有49个参考标签，分为七行，每行有七个参考标签。放置的七个待定位标签分别为第一个待定位标签A1、第二个待定位标签A2、第三个待定位标签A3、第四个待定位标签A4、第五个待定位标签A5、第六个待定位标签A6、第七个待定位标签A7。As shown in Figure 1, four card readers (A card reader, B card reader, C card reader, D card reader) are placed on the four corners of the indoor environment, and they are evenly distributed around as far as possible. There are 49 reference tags placed at equal intervals of 1m in the environmental space, divided into seven rows, and each row has seven reference tags. The seven tags to be positioned are the first tag to be positioned A1, the second tag to be positioned A2, the third tag to be positioned A3, the fourth tag to be positioned A4, the fifth tag to be positioned A5, the Six tags to be positioned A6, and the seventh tag to be positioned A7.

为了对第一个待定位标签A1进行估计位置采用上述的方法具体步骤有：In order to estimate the position of the first tag A1 to be located using the above method, the specific steps are as follows:

先由四个读卡器分别对49个参考标签进行采集其接收信号强度值Firstly, the received signal strength values of 49 reference tags are collected by four card readers respectively.

$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>4</span>4</span>}}<span><span>\}</span>\}</span><span><span>,</span>,</span>$$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>4</span>4</span>}}<span><span>\}</span>\}</span><span><span>,</span>,</span>$$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>4</span>4</span>}}<span><span>\}</span>\}</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span><span><span>\&CenterDot;</span>\&Center\; Dot;</span>\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>49</span>49</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>3</span>3</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>4</span>4</span>}}<span><span>\}</span>\}</span><span><span>;</span>;</span>$

然后由四个读卡器分别对第一个待定位标签A1进行采集其接收信号强度值Then the four card readers respectively collect the received signal strength value of the first tag A1 to be located

$\stackrel{<span><span>\&RightArrow;</span>\&Right\; Arrow;</span>}{{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>A</span>A</span>}\mathrm{<span><span>1</span>1</span>}}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>1</span>1</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>2</span>2</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>S</span><figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout></span>}}_{\mathrm{<span><span>3</span>3</span>}}{<span><span>,</span>,</span>\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>4</span>4</span>}}<span><span>\}</span>\}</span><span><span>;</span>;</span>$

然后将参考标签强度$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_1}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_2}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_3}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\}\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_{49}}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$待定位标签强度$\stackrel{\&RightArrow;}{S_{A1}}=\{S_1,S_2,S_3{,S}_4\}$传送给数据采集器；Then refer to the label strength$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_1}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_2}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_3}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\}\&Center\; Dot;\&Center\; Dot;\&CenterDot;\&Center\; Dot;\&CenterDot;\&CenterDot;\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_{49}}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$ Label strength to be located$\stackrel{\&Right\; Arrow;}{{\mathrm{<figure-callout\; label="S\; A"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout>}}_A}=\{{\mathrm{<figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout>}}_1,{\mathrm{<figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout>}}_2,{\mathrm{<figure-callout\; label="S"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">S</figure-callout>}}_3{,S}_4\}$ sent to the data collector;

数据采集器对接收的参考标签强度$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_1}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_2}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_3}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\}\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_{49}}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$待定位标签强度$\stackrel{\&RightArrow;}{S_{A1}}=\{S_1,S_2,S_3{,S}_4\}$依据欧几里德距离度量获得关于第1个参考标签与第一个待定位标签A1的距离度量$E_{A1,1}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}},$第2个参考标签与第一个待定位标签A1的距离度量$E_{A1,2}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}},$第3个参考标签与第一个待定位标签A1的距离度量$E_{A1,3}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;$第49个参考标签与第一个待定位标签A1的距离度量The strength of the reference tag received by the data logger against the$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_1}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_2}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$$\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_3}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\}\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\stackrel{\&Right\; Arrow;}{{\mathrm{\&theta;}}_{49}}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3,{\mathrm{\&theta;}}_4\},$ Label strength to be located$\stackrel{\&Right\; Arrow;}{S_{A1}}=\{S_1,S_2,S_3{,S}_4\}$ Obtain the distance metric between the first reference tag and the first tag A1 to be located according to the Euclidean distance metric${\mathrm{E.}}_{A1,1}={\left(\underset{i=1}{\overset{\mathrm{no}}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}},$ The distance measure between the second reference tag and the first tag A1 to be located${\mathrm{E.}}_{A1,2}={\left(\underset{i=1}{\overset{\mathrm{no}}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}},$ The distance measure between the third reference tag and the first tag A1 to be located${\mathrm{E.}}_{A1,3}={\left(\underset{i=1}{\overset{\mathrm{no}}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}\&CenterDot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;\&Center\; Dot;$ The distance measure between the 49th reference tag and the first tag A1 to be located

${\mathrm{<span><span>E</span><figure-callout\; label="E.\; A"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}"><figure-callout\; label="E.\; A"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}">E.</figure-callout></figure-callout></span><figure-callout\; label="E.\; A"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}"><figure-callout\; label="E.\; A"\; filenames="S2007101793195E00011.png"\; state="\{\{state\}\}"></figure-callout></figure-callout>}}_{\mathrm{<span><span></span></span>}\mathrm{<span><span></span></span>}}<span><span>=</span>=</span>{<span><span>(</span>(</span>\underset{\mathrm{<span><span>i</span>i</span>}<span><span>=</span>=</span>\mathrm{<span><span>1</span>1</span>}}{\overset{\mathrm{<span><span>n</span>no</span>}}{\mathrm{<span><span>\&Sigma;</span>\&Sigma;</span>}}}{<span><span>(</span>(</span>{\mathrm{<span><span>\&theta;</span>\&theta;</span>}}_{\mathrm{<span><span>i</span>i</span>}}<span><span>-</span>-</span>{\mathrm{<span><span>S</span>S</span>}}_{\mathrm{<span><span>i</span>i</span>}}<span><span>)</span>)</span>}^{\mathrm{<span><span>2</span>2</span>}}<span><span>)</span>)</span>}^{\frac{\mathrm{<span><span>1</span>1</span>}}{\mathrm{<span><span>2</span>2</span>}}}<span><span>;</span>;</span>$

对上述获得的49个参考标签与第一个待定位标签A1的距离度量进行从小到大排序；并选出最小的四个距离度量所对应的四个参考标签(9号参考标签、10号参考标签、16号参考标签、17号参考标签)；所述9号参考标签、10号参考标签、16号参考标签、17号参考标签即为距第一个待定位标签A1最近的四个近邻标签；Sorting the distance metrics between the 49 reference tags obtained above and the first tag A1 to be located from small to large; and selecting four reference tags corresponding to the smallest four distance metrics (No. label, No. 16 reference tag, No. 17 reference tag); the No. 9 reference tag, No. 10 reference tag, No. 16 reference tag, and No. 17 reference tag are the four nearest neighbor tags from the first tag A1 to be located ;

以B读卡器为原点，A读卡器方向为X轴正方向，C读卡器方向为Y轴正方向，则有9号参考标签的位置坐标为(3，7)、10号参考标签的位置坐标为(4，7)、16号参考标签的位置坐标为(3，6)、17号参考标签的位置坐标为(4，6)。Take card reader B as the origin, the direction of card reader A is the positive direction of X axis, and the direction of card reader C is the positive direction of Y axis, then the position coordinates of No. 9 reference tag are (3, 7), and No. 10 reference tag The position coordinates of thereference label 16 are (4, 7), the position coordinates of thereference label 16 are (3, 6), and the position coordinates of thereference label 17 are (4, 6).

则有第一个待定位标签A1的估计位置在9号参考标签、10号参考标签、16号参考标签、17号参考标签的确定的范围中。最后根据9号参考标签与第一个待定位标签A1的距离度量E_A1，9、10号参考标签与第一个待定位标签A1的距离度量E_A1，10、16号参考标签与第一个待定位标签A1的距离度量E_A1，16、17号参考标签与第一个待定位标签A1的距离度量E_A1，17的大小来确定第一个待定位标签A1的具体位置。Then the estimated position of the first tag to be located A1 is within the determined range of the No. 9 reference tag, No. 10 reference tag, No. 16 reference tag, and No. 17 reference tag. Finally, according to the distance measure E A1 between the No. 9 reference tag and the first tag A1 to be positioned, the distance measure E A1 between the_{No. 9} and No. 10 reference tags and the first tag A1 to be positioned,_{No. 10} and No. 16 reference tags The specific position of the first tag A1 to be located is determined by the distance measure E_A1,16 and 17 of the tag A1 to be located and the distance measure E_A1,17 between the tag A1 to be located and the first tag A1 to be located.

针对第二个待定位标签A2、第三个待定位标签A3、第四个待定位标签A4、第五个待定位标签A5、第六个待定位标签A6、第七个待定位标签A7分别采用上述的相同方法进行定位。For the second label to be located A2, the third label to be located A3, the fourth label to be located A4, the fifth label to be located A5, the sixth label to be located A6, and the seventh label to be located A7 respectively use Positioning in the same way as above.

则有：第二个待定位标签A2的估计位置在11号参考标签、12号参考标签、18号参考标签、19号参考标签的确定的范围中。最后根据11号参考标签与第二个待定位标签A2的距离度量E_A2，11、12号参考标签与第二个待定位标签A2的距离度量E_A2，12、18号参考标签与第二个待定位标签A2的距离度量E_A2，18、19号参考标签与第二个待定位标签A2的距离度量E_A2，19的大小来确定第二个待定位标签A2的具体位置。Then there is: the estimated position of the second to-be-located tag A2 is within the determined range of the No. 11 reference tag, No. 12 reference tag, No. 18 reference tag, and No. 19 reference tag. Finally, according to the distance measure E A2 between the No. 11 reference tag and the second tag A2 to be positioned, the distance measure E A2 between_{No. 11} and No. 12 reference tags and the second tag A2 to be positioned,_{No. 12} and No. 18 reference tags and the second The distance measure E_A2,18 of the tag A2 to be positioned and the distance measure E_A2,19 of the reference tag A2 and the second tag A2 to be positioned are used to determine the specific position of the second tag A2 to be positioned.

则有：第三个待定位标签A3的估计位置在15号参考标签、16号参考标签、22号参考标签、23号参考标签的确定的范围中。最后根据15号参考标签与第三个待定位标签A3的距离度量E_A3，15、16号参考标签与第三个待定位标签A3的距离度量E_A3，16、22号参考标签与第三个待定位标签A3的距离度量E_A3，22、23号参考标签与第三个待定位标签A3的距离度量E_A3，23的大小来确定第三个待定位标签A3的具体位置。Then there is: the estimated position of the third tag to be located A3 is within the determined range of the No. 15 reference tag, No. 16 reference tag, No. 22 reference tag, and No. 23 reference tag. Finally, according to the distance measure E A3 between the No. 15 reference tag and the third tag A3 to be positioned, the distance measure E A3 between No.₁₅ and No. 16 reference tags and the third tag A3 to be positioned,_{No. 16} and No. 22 reference tags and the third The distance metric E_A3,22 of the tag A3 to be located and the distance metric E_A3,23 between the No. 23 reference tag and the third tag A3 to be located are used to determine the specific position of the third tag A3 to be located.

则有：第四个待定位标签A4的估计位置在25号参考标签、26号参考标签、32号参考标签、33号参考标签的确定的范围中。最后根据25号参考标签与第四个待定位标签A4的距离度量E_A4，25、26号参考标签与第四个待定位标签A4的距离度量E_A4，26、32号参考标签与第四个待定位标签A4的距离度量E_A4，33、33号参考标签与第四个待定位标签A4的距离度量E_A4，34的大小来确定第四个待定位标签A4的具体位置。Then there is: the estimated position of the fourth tag to be located A4 is within the determined range of the No. 25 reference tag, No. 26 reference tag, No. 32 reference tag, and No. 33 reference tag. Finally, according to the distance measure E A4 between the No. 25 reference tag and the fourth tag A4 to be positioned, the distance measure E_A4 between No. 25 and No. 26 reference tags and the fourth tag A4 to be positioned,_{No. 26} and No. 32 reference tags and the fourth tag A4 The distance measure E_A4,33 of the tag A4 to be positioned and the distance measure E_A4,34 between the No. 33 reference tag and the fourth tag A4 to be positioned determine the specific position of the fourth tag A4 to be positioned.

则有：第五个待定位标签A5的估计位置在30号参考标签、31号参考标签、37号参考标签、38号参考标签的确定的范围中。最后根据30号参考标签与第五个待定位标签A5的距离度量E_A5，30、31号参考标签与第五个待定位标签A5的距离度量E_A5，31、37号参考标签与第五个待定位标签A5的距离度量E_A5，37、38号参考标签与第五个待定位标签A5的距离度量E_A5，38的大小来确定第五个待定位标签A5的具体位置。Then there is: the estimated position of the fifth tag to be located A5 is within the determined range of the No. 30 reference tag, No. 31 reference tag, No. 37 reference tag, and No. 38 reference tag. Finally, according to the distance measure E A5 between the No. 30 reference tag and the fifth tag A5 to be positioned, the distance measure E A5 between the No.₃₀ and No. 31 reference tags and the fifth tag A5 to be positioned,_{No. 31} and No. 37 reference tags and the fifth The specific position of the fifth tag A5 to be located is determined by the distance measure E_A5,37 and 38 of the tag A5 to be located and the distance measure E_A5,38 of the fifth tag A5 to be located.

则有：第六个待定位标签A6的估计位置在38号参考标签、39号参考标签、45号参考标签、46号参考标签的确定的范围中。最后根据38号参考标签与第六个待定位标签A6的距离度量E_A6，38、39号参考标签与第六个待定位标签A6的距离度量E_A6，39、45号参考标签与第六个待定位标签A6的距离度量E_A6，45、46号参考标签与第六个待定位标签A6的距离度量E_A6，46的大小来确定第六个待定位标签A6的具体位置。Then there is: the estimated position of the sixth tag to be located A6 is within the determined range of the No. 38 reference tag, No. 39 reference tag, No. 45 reference tag, and No. 46 reference tag. Finally, according to the distance measure E A6 between the No. 38 reference tag and the sixth tag A6 to be positioned, the distance measure E A6 between No.₃₈ and No. 39 reference tags and the sixth tag A6 to be positioned,_{No. 39} and No. 45 reference tags and the sixth The distance metric E_A6,45 of the tag A6 to be located and the distance metric E_A6,46 between the reference tag A6 and the sixth tag A6 to be located are used to determine the specific position of the sixth tag A6 to be located.

则有：第七个待定位标签A7的估计位置在41号参考标签、42号参考标签、48号参考标签、49号参考标签的确定的范围中。最后根据41号参考标签与第七个待定位标签A7的距离度量E_47，41、42号参考标签与第七个待定位标签A7的距离度量E_A7，42、48号参考标签与第七个待定位标签A7的距离度量E_A7，48、49号参考标签与第七个待定位标签A7的距离度量E_A7，49的大小来确定第七个待定位标签A7的具体位置。Then there is: the estimated position of the seventh tag to be located A7 is within the determined range of the No. 41 reference tag, No. 42 reference tag, No. 48 reference tag, and No. 49 reference tag. Finally, according to thedistance measure E 47 between the No. 41 reference tag and the seventh tag A7 to be positioned, the distance measure E A7_between No.₄₁ and No. 42 reference tags and the seventh tag A7 to be positioned The specific position of the seventh tag A7 to be located is determined by the distance measure E_A7,48 of the tag A7 to be located, and the distance measure E_A7,49 between the reference tag No. 49 and the seventh tag A7 to be located.

本发明利用的RSS参数，即RFID读卡器阅读标签时所接收到的无线信号强度，是一个和距离相关的通信参数，可以有效的应用于无线定位系统之中。The RSS parameter used in the present invention, that is, the wireless signal strength received by the RFID card reader when reading the tag, is a communication parameter related to distance, and can be effectively applied to the wireless positioning system.

本发明可以有效的实现室内电子标签定位，利用发明中提出的普适性算法，可以有效的抑制由标签间差异带来的误差，将定位精度提高到标签无差异时的水平，能够满足该领域实际需求。该发明可以应用于很多无线定位系统中，具有良好的实用推广价值。The present invention can effectively realize the positioning of indoor electronic tags. Using the universal algorithm proposed in the invention, it can effectively suppress the error caused by the difference between the tags, and improve the positioning accuracy to the level when there is no difference between the tags, which can meet the requirements of this field. Actual demand. The invention can be applied to many wireless positioning systems, and has good practical promotion value.

Claims (2)

1. radio frequency recognition indoor position finding and detection method based on received signal intensity is characterized in that comprising following several steps:

The first step: respectively b reference label gathered its received signal intensity level by n card reader earlierAnd$\stackrel{\&RightArrow;}{{\mathrm{\&theta;}}_b}=\{{\mathrm{\&theta;}}_1,{\mathrm{\&theta;}}_2,{\mathrm{\&theta;}}_3{\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\mathrm{\&theta;}}_n\};$

Respectively a label to be positioned gathered its received signal intensity level by n card reader then

And

$\stackrel{\&RightArrow;}{S_a}=\{S_1,S_2,S_3\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;S_n\};$

Then with reference label intensity

Label intensity to be positioned

Send data acquisition unit to;

Second step: the reference label intensity of data acquisition unit to receiving

Label intensity to be positioned

According to euclidean distance metric$E_{a,b}={\left(\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&theta;}}_i-S_i)}^2\right)}^{\frac{1}{2}}$Obtain the Euclidean distance vector of a label to be positioned;

I represents i card reader, θ_iRepresent the reference label received signal intensity level read on i the card reader, S_iRepresent the label received signal intensity level to be positioned read on i the card reader;

The 3rd step: repeat the euclidean distance metric E that second step obtained all m reference label and a label to be positioned_{A, j}, and j ∈ (1, m), j represents j reference label;

The 4th step: to the 1st reference label of the 3rd step acquisition and the distance metric E of a label to be positioned_{A, 1}, the 2nd reference label and a label to be positioned distance metric E_{A, 2}, the 3rd reference label and a label to be positioned distance metric E_{A, 3}The distance metric E of m reference label and a label to be positioned_{A, m}Sort from small to large;

The 5th step: select minimum pairing four reference label of four distance metrics in the 4th step; Described four reference label are apart from a four nearest neighbour's labels of label to be positioned;

The 6th step:, calculate the estimated position of a label to be positioned according to these four position coordinateses that neighbour's label is known.

2. the radio frequency recognition indoor position finding and detection method based on received signal intensity according to claim 1 is characterized in that: after the first step finishes, carry out the processing of universality signal space model before the beginning of second step; Described universality signal space model is:

//n: the quantity of card reader in the system

//REFTAGNUM: the quantity that participates in the reference label of location in the system

//rssm: corrected parameter

//TAG_TRACK_RSS: the signal space of label to be positioned

//TAG_REF_RSS (:, i): the signal space of i reference label

//sum (T): to the element summation of signal space vector T

for(i＝1：REFTAGNUM)

rssm＝(sum(TAG_TRACK_RSS)-sum(TAG_REF_RSS(:，i)))/n；

TAG_REF_RSS(:，i)＝TAG_REF_RSS(:，i)+rssm；

End。

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