CN107102308A - A kind of distributed radar anomeric signals level fusion object detection method - Google Patents
A kind of distributed radar anomeric signals level fusion object detection method Download PDFInfo
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Abstract
本发明属于雷达目标检测技术领域，公开了一种分布式雷达异构信号级融合目标检测方法，包括：设置分布式雷达系统包含N个局部雷达站以及一个融合检测中心；构造每个局部雷达站的局部检测统计量；设置分布式雷达系统的虚警概率pf；每个局部雷达站根据其对应的局部检测统计量以及分布式雷达系统的虚警概率，计算该局部雷达站的信噪比加权系数；设置融合判决门限，融合检测中心将N个局部雷达站的局部检测统计量进行信噪比加权，得到融合后的检测统计量；若融合后的检测统计量大于融合判决门限，则确定检测到目标，能够目标的检测性能。
The invention belongs to the technical field of radar target detection, and discloses a distributed radar heterogeneous signal level fusion target detection method, comprising: setting a distributed radar system including N local radar stations and a fusion detection center; constructing each local radar station The local detection statistics; set the false alarm probability p f of the distributed radar system; each local radar station calculates the signal-to-noise ratio of the local radar station according to its corresponding local detection statistics and the false alarm probability of the distributed radar system Weighting coefficient; set the fusion judgment threshold, and the fusion detection center will carry out signal-to-noise ratio weighting on the local detection statistics of N local radar stations to obtain the fusion detection statistics; if the fusion detection statistics are greater than the fusion judgment threshold, then determine The target is detected, capable of target detection performance.
Description
技术领域technical field
本发明属于雷达目标检测技术领域，尤其涉及一种分布式雷达异构信号级融合目标检测方法。The invention belongs to the technical field of radar target detection, and in particular relates to a distributed radar heterogeneous signal level fusion target detection method.
背景技术Background technique
分布式雷达是雷达领域的热门话题，是目标检测数据融合算法的关键问题。Distributed radar is a hot topic in the field of radar, and it is a key issue in target detection data fusion algorithms.
传统的分布式雷达目标检测融合算法在各个局部雷达站具有相同的参数及统计量构造的条件下具有较好的检测性能，但是当局部雷达站的参数有差异时，也就是各个通道(每个局部雷达站也称为一个通道)的信噪比损失不同时，传统的检测算法的检测性能就会恶化，并且这种恶化程度随着上面所述的差异的扩大而变大，而实际上的各局部雷达站不一定都是同型号雷达且参数以及统计量的构造方式也不一定相同，因而导致了各局部雷达站的单站检测性能不一致，当实际的差异较大时，传统的分布式雷达目标检测算法就不能满足高效的检测目标的任务。The traditional distributed radar target detection fusion algorithm has better detection performance under the condition that each local radar station has the same parameters and statistical structure, but when the parameters of the local radar stations are different, that is, each channel (each When the signal-to-noise ratio loss of a local radar station (also known as a channel) is different, the detection performance of the traditional detection algorithm will deteriorate, and the degree of deterioration will become larger with the expansion of the above-mentioned difference, while the actual The local radar stations are not necessarily the same type of radar and the construction methods of parameters and statistics are not necessarily the same, which leads to the inconsistency of the single-station detection performance of each local radar station. When the actual difference is large, the traditional distributed Radar target detection algorithms cannot meet the task of detecting targets efficiently.
发明内容Contents of the invention
针对上述现有技术的缺点，本发明的目的在于提供一种分布式雷达异构信号级融合目标检测方法，能够改善在不同局部雷达站参数有差异及构造的检测统计量分布差异较大时所导致的检测性能恶化问题。Aiming at the shortcomings of the above-mentioned prior art, the object of the present invention is to provide a distributed radar heterogeneous signal-level fusion target detection method, which can improve the detection statistics when different local radar station parameters are different and the distribution of the detection statistics of the structure is greatly different. The resulting deterioration of detection performance.
为达到上述目的，本发明采用如下技术方案予以实现。In order to achieve the above object, the present invention adopts the following technical solutions to achieve.
一种分布式雷达异构信号级融合目标检测方法，所述方法包括：A distributed radar heterogeneous signal level fusion target detection method, the method comprising:
步骤1，设置分布式雷达系统包含N个局部雷达站以及一个融合检测中心；并构造每个局部雷达站的满足恒虚警性质(恒虚警性质是指虚警概率只与判决门限有关，不随背景噪声功率的波动而变化)的局部检测统计量；Step 1, set the distributed radar system to include N local radar stations and a fusion detection center; and construct each local radar station to satisfy the constant false alarm property (constant false alarm property means that the false alarm probability is only related to the judgment threshold, not The local detection statistic that changes with the fluctuation of the background noise power);
步骤2，设置所述分布式雷达系统的总体虚警概率pf，每个局部雷达站评估检测性能曲线的虚警概率与所述分布式雷达系统的总体虚警概率相等；Step 2, setting the overall false alarm probability p f of the distributed radar system, the false alarm probability of each local radar station evaluation detection performance curve is equal to the overall false alarm probability of the distributed radar system;
步骤3，每个局部雷达站根据其对应的局部检测统计量以及局部雷达站评估检测性能曲线的虚警概率pf，计算该局部雷达站的信噪比加权系数；Step 3, each local radar station calculates the SNR weighting coefficient of the local radar station according to its corresponding local detection statistics and the false alarm probability p f of the local radar station evaluation detection performance curve;
步骤4，设置融合判决门限,所述融合检测中心根据每个局部雷达站的局部检测统计量以及该局部雷达站的信噪比加权系数，将N个局部雷达站的局部检测统计量进行信噪比加权，得到融合后的检测统计量；Step 4, setting the fusion decision threshold, the fusion detection center performs signal-to-noise analysis on the local detection statistics of N local radar stations according to the local detection statistics of each local radar station and the SNR weighting coefficient of the local radar station. Ratio weighted to obtain the fused detection statistics;
若所述融合后的检测统计量大于所述融合判决门限，则确定检测到目标。If the fused detection statistic is greater than the fused decision threshold, it is determined that the target is detected.
本发明技术方案的特点和进一步的改进为：Features and further improvements of the technical solution of the present invention are:
(1)步骤1中，构造每个局部雷达站的满足恒虚警性质的局部检测统计量的方法有很多种，例如下面的这种构造方法得到的局部检测统计量就满足恒虚警的性质：(1) In step 1, there are many ways to construct the local detection statistics of each local radar station that satisfy the constant false alarm property. For example, the local detection statistics obtained by the following construction method satisfy the constant false alarm property :
第n个局部雷达站的局部检测统计量qn表示为：The local detection statistic q n of the nth local radar station is expressed as:
其中，Dn表示第n个局部雷达站的采样单元的采样值，n＝1,...,N，xni表示第n个局部雷达站的第i个参考单元的采样值，且i＝1,...,ln，ln为第n个局部雷达站的参考单元总个数。Among them, D n represents the sampling value of the sampling unit of the nth local radar station, n=1,...,N, x ni represents the sampling value of the ith reference unit of the nth local radar station, and i= 1,...,l n , l n is the total number of reference units of the nth local radar station.
(2)步骤3具体包括如下子步骤：(2) Step 3 specifically includes the following sub-steps:
(3a)在所述局部雷达站评估检测性能曲线的虚警概率pf条件下，第n个局部雷达站根据其对应的局部检测统计量qn做单站检测，得到对应该局部雷达站的检测性能曲线；所述检测性能曲线的横坐标为信噪比，纵坐标为目标存在时的检测概率值；(3a) Under the condition of the false alarm probability p f of the local radar station evaluation detection performance curve, the nth local radar station performs single-station detection according to its corresponding local detection statistic qn, and obtains the corresponding local radar station Detection performance curve; the abscissa of the detection performance curve is the signal-to-noise ratio, and the ordinate is the detection probability value when the target exists;
(3b)设置目标存在的预设概率值pd，第n个局部雷达站根据所述目标存在的预设概率值pd，在该局部雷达站的检测性能曲线上确定出所述目标存在的预设概率值pd对应的信噪比SNRn；(3b) Set the preset probability value p d of the existence of the target, and the nth local radar station determines the existence of the target on the detection performance curve of the local radar station according to the preset probability value p d of the existence of the target The signal-to-noise ratio SNR n corresponding to the preset probability value p d ;
(3c)令n＝1,...,N，从而分别得到N个局部雷达站在目标存在的预设概率值处对应的信噪比；(3c) Make n=1,...,N, thereby obtain the signal-to-noise ratios corresponding to the preset probability values of target existence at N local radar stations respectively;
(3d)则第n个局部雷达站的信噪比加权系数其中，SNRmin表示N个局部雷达站在目标存在的预设概率值处对应的信噪比中的最小值。(3d) The SNR weighting coefficient of the nth local radar station Wherein, SNR min represents the minimum value of the signal-to-noise ratio corresponding to the preset probability value of the existence of the target at the N local radar stations.
(3)子步骤(3d)中，(3) In sub-step (3d),
第n个局部雷达站的信噪比加权系数w(n)的另一种表示方式为：Another expression of the SNR weighting coefficient w(n) of the nth local radar station is:
其中， in,
(4)步骤4具体为：(4) Step 4 is specifically:
(4a)设置融合判决门限η；(4a) setting fusion decision threshold η;
(4b)所述融合检测中心根据每个局部雷达站的局部检测统计量以及该局部雷达站的信噪比加权系数，将N个局部雷达站的局部检测统计量进行信噪比加权，得到融合后的检测统计量t： (4b) The fusion detection center performs SNR weighting on the local detection statistics of N local radar stations according to the local detection statistics of each local radar station and the SNR weighting coefficient of the local radar station to obtain the fusion After the detection statistic t:
(4c)若融合后的检测统计量t大于融合判决门限η，则判定为检测到目标；若融合后的检测统计量t小于融合判决门限η，则判定为未检测到目标。(4c) If the fused detection statistic t is greater than the fusion decision threshold η, it is determined that the target is detected; if the fused detection statistic t is smaller than the fusion decision threshold η, it is determined that the target is not detected.
通过本发明的方法，可以在一定程度上降低分布式雷达异构信号级融合的检测性能恶化。Through the method of the invention, the detection performance deterioration of the heterogeneous signal level fusion of the distributed radar can be reduced to a certain extent.
附图说明Description of drawings
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.
图1为本发明实施例提供的一种分布式雷达异构信号级融合目标检测方法的流程示意图；FIG. 1 is a schematic flow diagram of a distributed radar heterogeneous signal level fusion target detection method provided by an embodiment of the present invention;
图2为本发明实施例提供的仿真实验中参数l1＝8,l2＝12,l3＝16,l4＝20时4个局部雷达站的检测性能曲线示意图；Fig. 2 is a schematic diagram of detection performance curves of four local radar stations when parameters l 1 =8, l 2 =12, l 3 =16, l 4 =20 in the simulation experiment provided by the embodiment of the present invention;
图3为本发明实施例提供的仿真实验中参数l1＝8,l2＝16,l3＝24,l4＝32时4个局部雷达站的检测性能曲线示意图；Fig. 3 is a schematic diagram of detection performance curves of four local radar stations when parameters l 1 =8, l 2 =16, l 3 =24, l 4 =32 in the simulation experiment provided by the embodiment of the present invention;
图4为本发明实施例提供的仿真试验中未进行信噪比加权和进行信噪比加权后的检测性能曲线对比示意图。FIG. 4 is a schematic diagram of comparison of detection performance curves without SNR weighting and SNR weighting in the simulation test provided by the embodiment of the present invention.
具体实施方式detailed description
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
本发明实施例提供一种分布式雷达异构信号级融合目标检测方法，如图1所示，所述方法包括：An embodiment of the present invention provides a distributed radar heterogeneous signal level fusion target detection method, as shown in Figure 1, the method includes:
步骤1，设置分布式雷达系统包含N个局部雷达站以及一个融合检测中心；并构造每个局部雷达站的满足恒虚警性质的局部检测统计量。Step 1. Set the distributed radar system to include N local radar stations and a fusion detection center; and construct the local detection statistics of each local radar station satisfying the constant false alarm property.
步骤1中，构造每个局部雷达站的局部检测统计量，选择如下构造方法但构造方法并不唯一，只要构造的局部检测统计量满足恒虚警性质都可以作为本发明实施例中所述的局部检测统计量。In step 1, the local detection statistics of each local radar station are constructed, and the following construction method is selected but the construction method is not unique. As long as the constructed local detection statistics satisfy the constant false alarm property, it can be used as the method described in the embodiment of the present invention Local detection statistics.
第n个局部雷达站的局部检测统计量qn表示为：The local detection statistic q n of the nth local radar station is expressed as:
其中，Dn表示第n个局部雷达站的采样单元的采样值，n＝1,...,N，xni表示第n个局部雷达站的第i个参考单元的采样值，且i＝1,...,ln，ln为第n个局部雷达站的参考单元总个数。Among them, D n represents the sampling value of the sampling unit of the nth local radar station, n=1,...,N, x ni represents the sampling value of the ith reference unit of the nth local radar station, and i= 1,...,l n , l n is the total number of reference units of the nth local radar station.
需要说明的是，每个局部雷达站具有一个采样单元，且采样单元中包含目标信号和噪声，且每个局部雷达站具有多个参考单元，且每个参考单元中只包含噪声。It should be noted that each local radar station has a sampling unit, and the sampling unit contains the target signal and noise, and each local radar station has multiple reference units, and each reference unit only contains noise.
具体的，假设tn是第n个局部雷达站接收到的观测值，第n个局部雷达站的局部检测统计量qn是观测值tn的单调变换函数，qn具有恒虚警性质(虚警概率只与判决门限有关，不随背景噪声功率的波动而变化)，qn幅度越大目标存在的可能性越大。Specifically, assuming that t n is the observation value received by the nth local radar station, the local detection statistic q n of the nth local radar station is a monotonic transformation function of the observation value t n , and q n has the property of constant false alarm ( The probability of false alarm is only related to the decision threshold, and does not change with the fluctuation of the background noise power), the larger the magnitude of qn , the greater the possibility of the existence of the target.
示例性的，当N个局部雷达站处于独立同分布零均值的高斯白噪声背景下，且目标回波信号为SwerlingΙ模型时，经过平方率检波器后采样单元Dn的概率密度函数和参考单元xni的概率密度函数服从指数分布，具体如下式：Exemplarily, when N local radar stations are in the Gaussian white noise background with independent identical distribution and zero mean value, and the target echo signal is a Swerling1 model, the probability density function of the sampling unit Dn after passing through the square rate detector and the probability density function of the reference unit x ni obey the exponential distribution, as follows:
λn表示第n个局部雷达站的信噪比(单位为1)，μ表示背景噪声功率水平，可推得第n个局部雷达站的局部检测统计量qn的累积分布函数Fqn(x)如下:λ n represents the signal-to-noise ratio of the nth local radar station (unit is 1), μ represents the background noise power level, and the cumulative distribution function F qn (x )as follows:
步骤2，设置所述分布式雷达系统的虚警概率pf，在求取局部雷达站的信噪比加权系数时的每个局部雷达站的虚警概率等于所述分布式雷达系统的虚警概率也为pf。Step 2, setting the false alarm probability p f of the distributed radar system, the false alarm probability of each local radar station is equal to the false alarm probability of the distributed radar system when calculating the SNR weighting coefficient of the local radar station The probability is also p f .
具体的，所述分布式雷达系统的虚警概率pf＝10-4。Specifically, the false alarm probability p f =10 -4 of the distributed radar system.
步骤3，每个局部雷达站根据其对应的局部检测统计量以及局部雷达站的虚警概率pf，计算该局部雷达站的信噪比加权系数。Step 3, each local radar station calculates the SNR weighting coefficient of the local radar station according to its corresponding local detection statistics and the false alarm probability p f of the local radar station.
步骤3具体包括如下子步骤：Step 3 specifically includes the following sub-steps:
(3a)在所述局部雷达站的虚警概率pf条件下，第n个局部雷达站根据其对应的局部检测统计量qn做单站检测(即该雷达目标检测系统只有一个雷达站)，得到对应该局部雷达站的检测性能曲线；所述检测性能曲线的横坐标为信噪比，纵坐标为目标存在时该单站雷达目标检测系统可检测到目标的检测概率值；(3a) Under the condition of the false alarm probability pf of the local radar station, the nth local radar station performs single-station detection according to its corresponding local detection statistic qn (that is, the radar target detection system has only one radar station) , to obtain the detection performance curve corresponding to the local radar station; the abscissa of the detection performance curve is the signal-to-noise ratio, and the ordinate is the detection probability value that the single-station radar target detection system can detect the target when the target exists;
具体的，将N个局部雷达站用自己的检测统计量qn做单站检测，判决方法如下：Specifically, the N local radar stations use their own detection statistics qn to perform single-station detection, and the judgment method is as follows:
ηn为第n个局部雷达站做单站检测时在虚警概率为pf时的检测门限(即在局部雷达站没有目标情况下qn的值大于ηn的概率为pf)，然后画出在虚警概率为pf时的N个单站雷达目标检测系统的检测性能曲线；η n is the detection threshold when the nth local radar station performs single-station detection when the false alarm probability is pf (that is, the probability that the value of qn is greater than ηn is pf when the local radar station has no target), and then Draw the detection performance curves of N single-station radar target detection systems when the false alarm probability is p f ;
(3b)设置目标存在的预设概率值pd，第n个局部雷达站根据所述目标存在的预设概率值pd，在该局部雷达站的检测性能曲线上确定出所述目标存在的预设概率值pd对应的信噪比SNRn；(3b) Set the preset probability value p d of the existence of the target, and the nth local radar station determines the existence of the target on the detection performance curve of the local radar station according to the preset probability value p d of the existence of the target The signal-to-noise ratio SNR n corresponding to the preset probability value p d ;
具体的，设置目标存在的预设概率值pd＝50％；Specifically, the preset probability value p d of the existence of the target is set = 50%;
(3c)令n＝1,...,N，从而分别得到N个局部雷达站在目标存在的预设概率值处对应的信噪比；(3c) Make n=1,...,N, thereby obtain the signal-to-noise ratios corresponding to the preset probability values of target existence at N local radar stations respectively;
(3d)则第n个局部雷达站的信噪比加权系数其中，SNRmin表示N个局部雷达站在目标存在的预设概率值处对应的信噪比中的最小值。(3d) The SNR weighting coefficient of the nth local radar station Wherein, SNR min represents the minimum value of the signal-to-noise ratio corresponding to the preset probability value of the presence of the target at the N local radar stations.
具体的，SNRn-SNRmin表示第n个局部雷达站的信噪比损失。Specifically, SNR n −SNR min represents the SNR loss of the nth local radar station.
子步骤(3d)中，In substep (3d),
第n个局部雷达站的信噪比加权系数w(n)的另一种表示方式为：Another expression of the SNR weighting coefficient w(n) of the nth local radar station is:
其中， in,
步骤4，设置融合判决门限，所述融合检测中心根据每个局部雷达站的局部检测统计量以及该局部雷达站的信噪比加权系数，将N个局部雷达站的局部检测统计量进行信噪比加权，得到融合后的检测统计量；Step 4, setting the fusion decision threshold, the fusion detection center performs signal-to-noise analysis on the local detection statistics of N local radar stations according to the local detection statistics of each local radar station and the SNR weighting coefficient of the local radar station. Ratio weighted to obtain the fused detection statistics;
若所述融合后的检测统计量大于所述融合判决门限，则确定检测到目标。If the fused detection statistic is greater than the fused decision threshold, it is determined that the target is detected.
步骤4具体为：Step 4 is specifically:
(4a)设置融合判决门限η；(4a) setting fusion decision threshold η;
具体的，η为在给定分布式雷达系统的虚警概率pf条件下求得的融合判决门限(即在没有目标情况下融合后的值大于η的概率为pf)；Specifically, η is the fusion decision threshold obtained under the condition of the false alarm probability p f of the given distributed radar system (that is, the probability that the fused value is greater than η when there is no target is p f );
(4b)所述融合检测中心根据每个局部雷达站的局部检测统计量以及该局部雷达站的信噪比加权系数，将N个局部雷达站的局部检测统计量进行信噪比加权，得到融合后的检测统计量t： (4b) The fusion detection center performs SNR weighting on the local detection statistics of N local radar stations according to the local detection statistics of each local radar station and the SNR weighting coefficient of the local radar station to obtain the fusion After the detection statistic t:
(4c)若融合后的检测统计量t大于融合判决门限η，则判定为检测到目标；若融合后的检测统计量t小于融合判决门限η，则判定为未检测到目标。(4c) If the fused detection statistic t is greater than the fusion decision threshold η, it is determined that the target is detected; if the fused detection statistic t is smaller than the fusion decision threshold η, it is determined that the target is not detected.
仿真实验：Simulation:
使用MATLAB软件，画出4个局部雷达站在虚警概率为10-4时的检测性能曲线，按照本发明技术方案求出每个局部雷达站对应的信噪比加权系数，用蒙多卡洛法再画出未加权和加权后的检测性能曲线。Use MATLAB software, draw the detection performance curve when the false alarm probability of 4 local radar stations is 10 -4 , obtain the SNR weighting coefficient corresponding to each local radar station according to the technical scheme of the present invention, use Monte Carlo Then draw the unweighted and weighted detection performance curves.
由图2、3可知，对于单站检测，其检测性能会随着参考单元的增加而变好，因而在相同的检测概率时，基于不同的参考单元下的单站检测的信噪比不一样，参考单元少的与参考单元多的单站检测有一个相对信噪比损失。It can be seen from Figures 2 and 3 that for single-station detection, its detection performance will improve with the increase of reference units. Therefore, at the same detection probability, the signal-to-noise ratio of single-station detection based on different reference units is different , there is a relative SNR loss in the single-station detection with fewer reference units and with more reference units.
由图4可知，该算法进行信噪比加权后的检测性能比未加权好，在参数l1＝8,l2＝12,l3＝16,l4＝20下，在目标存在的预设概率值为50％时，信噪比加权方式为w1时相对于未加权的时候有大约0.3dB的增益，加权方式为w2时大约有0.25dB的增益。在参数l1＝8,l2＝16,l3＝24,l4＝32下，在目标存在的预设概率值为50％时，信噪比加权方式为w1时相对于未加权的时候有大约0.45dB的增益，加权方式为w2时大约有0.4dB的增益。由上可知参数差异越大增益效果越好，并且该算法提出的信噪比加权中w1加权方式比w2好。It can be seen from Fig. 4 that the detection performance of the algorithm after SNR weighting is better than that without weighting. Under the parameters l 1 =8, l 2 =12, l 3 =16, l 4 =20, the preset When the probability value is 50%, there is about 0.3dB gain when the SNR weighting method is w1, and about 0.25dB gain when the weighting method is w2. Under the parameters l 1 =8, l 2 =16, l 3 =24, l 4 =32, when the preset probability value of target existence is 50%, the SNR weighted mode is w1 relative to the unweighted time There is a gain of about 0.45dB, and there is a gain of about 0.4dB when the weighting method is w2. It can be seen from the above that the greater the parameter difference, the better the gain effect, and the w1 weighting method in the SNR weighting proposed by this algorithm is better than w2.
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。Those of ordinary skill in the art can understand that all or part of the steps to realize the above method embodiments can be completed by hardware related to program instructions, and the aforementioned programs can be stored in computer-readable storage media. When the program is executed, the execution includes The steps of the above-mentioned method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other various media that can store program codes.
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.
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