WO2019179084A1 - 一种基于噪声消除的到达时间估计方法 - Google Patents

一种基于噪声消除的到达时间估计方法 Download PDF

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WO2019179084A1
WO2019179084A1 PCT/CN2018/110448 CN2018110448W WO2019179084A1 WO 2019179084 A1 WO2019179084 A1 WO 2019179084A1 CN 2018110448 W CN2018110448 W CN 2018110448W WO 2019179084 A1 WO2019179084 A1 WO 2019179084A1
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power
noise
arrival time
chip
rank
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冯义志
杨平平
张军
宁更新
季飞
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华南理工大学
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Priority to US16/966,123 priority patent/US10972141B2/en
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06Receivers
    • H04B1/10Means associated with receiver for limiting or suppressing noise or interference
    • H04B1/12Neutralising, balancing, or compensation arrangements
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06Receivers
    • H04B1/10Means associated with receiver for limiting or suppressing noise or interference
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S11/00Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/02Systems for determining distance or velocity not using reflection or reradiation using radio waves
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S5/00Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02Position-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
    • G01S5/0205Details
    • G01S5/0215Interference
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06Receivers
    • H04B1/10Means associated with receiver for limiting or suppressing noise or interference
    • H04B1/1027Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal

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  • the invention belongs to the field of wireless communication, and relates to a pulse ultra-wideband signal localization technology, in particular to a method for estimating an arrival time based on noise cancellation.
  • Pulse ultra-wideband signals have the characteristics of high temporal resolution and strong penetrating power. In theory, they can provide centimeter or even millimeter-scale ranging and positioning accuracy, and do not require modulation during transmission, and the system complexity is low, so high precision In the positioning technology, it has received extensive attention.
  • the time of arrival (TOA) estimation can fully utilize the advantages of pulsed ultra-wideband technology, has high ranging and positioning accuracy, and achieves low complexity, and is a common method for pulsed ultra-wideband positioning technology.
  • the key to the TOA estimation is how to detect the first path (FP) in the multipath channel according to the receiver signal, that is, the direct path, and it is especially important to eliminate the noise interference in the signal at the receiving end.
  • FP first path
  • MES Maximum Energy Selection
  • TC Cross Threshold
  • the MES algorithm takes the time at which the largest energy block is located as the TOA estimate.
  • the first path is often not the strongest energy path, which makes the MES algorithm performance poor. Therefore, many methods are based on the TC algorithm to detect the first path.
  • the TC algorithm compares the output of the energy detection receiver with a fixed threshold, and the time at which the first energy block spans the threshold is taken as an estimate of the TOA. But this algorithm requires an optimal threshold that is obtained through a complex design. In the case where the channel model is complex and the channel prior information is unknown, it is very difficult to set such an optimal threshold.
  • the invention number "CN103297087”, published on September 11, 2013, "a method for estimating the arrival time of an ultra-wideband positioning system”, provides a threshold calculation model based on constant false alarm rate constraints, although the calculation process
  • the energy sequence is pre-sorted to reduce the amount of computation to complete the arrival time estimate, but the invention does not eliminate noise interference, and the method involves an iterative process for decomposing the optimal threshold with high time complexity.
  • the invention patent CN106131949A published on November 16, 2016, "A method for estimating the arrival time based on energy mean detection” provides a maximum average energy minimum value based on time average to set the optimal normalization threshold. Thus, the method of setting the threshold is set.
  • the invention number "CN106879068A”, published on June 20, 2017, "A method for estimating the arrival time of a signal in a strong multipath environment” reduces the noise interference and reduces the noise by normalizing the received signal. The effect of signal transmission loss, but the invention can only suppress burst noise in the received signal.
  • the existing TOA estimation method does not fully eliminate the noise influence, and the threshold setting method is complicated, and there are performance defects in actual situations, and the high-precision positioning algorithm needs to be improved.
  • the object of the present invention is to solve the above-mentioned drawbacks in the prior art, and to provide an arrival time estimation method based on noise cancellation, which improves the TOA estimation accuracy by performing denoising processing on the receiving end signal.
  • An arrival time estimation method based on noise cancellation comprising the following steps:
  • the transmitting end sends an ultra-wideband pulse sequence
  • the received ultra-wideband signal r(t) is
  • ⁇ (t) is an ultra-wideband pulse
  • the pulse width is equal to the chip period T c
  • T s , T f are the symbol period and the frame period of the transmitted signal, respectively, and the time is set before the position of the ultra-wideband pulse in each frame
  • ⁇ guard is used as the guard interval
  • n(t) means the mean is zero
  • the bilateral power spectral density is Complex plus Gaussian white noise
  • Is the unit impulse response of the channel, where ⁇ l and ⁇ l are the complex attenuation factor and delay of the lth path, respectively, L is the multipath number, and ⁇ (t) is the Dirac ⁇ function.
  • T s , T f , T c are the symbol period, frame period and chip period of the transmitted signal, respectively, and ⁇ position takes values in the range of (0, T c ), indicating the sampling position within the chip, r bpf ( t) is the output of the bandpass filter, That is, the power signal obtained after passing through the square law detector.
  • V k in the n-th element V n, k the serial number in the ordered sequence W k is the rank of the element, referred to as
  • the setting of the decision threshold ⁇ includes the following steps:
  • selecting the time chip includes the following steps:
  • S701 sequentially compare the element Z(k) in the Z with the decision threshold ⁇ according to the increasing order of k;
  • the element that first exceeds the decision threshold ⁇ is recorded as the time chip of Z(k 0 ), Z(k 0 )
  • the position is the estimated value of the arrival time.
  • the subscript of the time chip where the element Z(k 0 ) is located is represented as k 0 , that is, the time chip in which the element Z(k 0 ) is located is the k 0th chip.
  • Estimated value of arrival time ⁇ by The calculation is ok.
  • the mean operation for the power sampling sequence proposed by the present invention can effectively eliminate the noise in the received signal and improve the accuracy of the arrival time estimation. Moreover, the noise cancellation method has independence and does not depend on the acquisition of channel prior information, and is applicable to an actual ultra-wideband positioning system.
  • the present invention employs a rank sum method for identifying ultra-wideband pulse signals and noise signals, rather than directly comparing the magnitudes of the two. This makes the identification process easier to operate, results are more accurate and reliable, and can effectively remove the effects of outliers.
  • the threshold setting method adopted by the present invention is simple in form, reliable and effective.
  • FIG. 1 is a flow chart of a noise cancellation based arrival time estimation method disclosed in the present invention
  • Figure 3 is a block diagram showing the structure of a pulse sequence emitted in the present invention.
  • This embodiment discloses a method for estimating the arrival time based on noise cancellation. As shown in FIG. 1 and FIG. 2, the implementation steps of the method are as follows:
  • N s represents the number of symbols of the transmitted signal
  • N f represents the number of frames in each symbol
  • N c represents the number of chips in each frame
  • the corresponding symbol period, frame period, and chip period are respectively recorded as T s , T f , T c .
  • the received ultra-wideband signal r(t) is bandpass filtered by a low noise amplifier, and then passed through a square law detector to obtain a power signal.
  • the power signal is then sampled to obtain a power sample sequence ⁇ A n,l,k ⁇ of the received signal.
  • the received ultra-wideband signal r(t) passes through the low noise amplifier and then passes through a bandpass filter to remove out-of-band noise.
  • n(t) means the mean is zero and the bilateral power spectral density is Complex plus Gaussian white noise, satisfying Where SNR represents the signal noise power ratio (in dB).
  • h(t) is the unit impulse response of the channel.
  • the channel model considered is the ultra-wideband channel of IEEE802.15.4a CM3, and the unit impulse response of the channel is
  • the relative time delay ⁇ k,l of the kth multipath component with respect to the arrival time T l of the first cluster satisfies the mixed Poisson distribution
  • the bandpass filtered received signal is passed through a square law detector to obtain a power signal, and the power signal is recorded as
  • Power sampling sequence A n,l,k Determining, wherein T s , T f are the symbol period and the frame period of the transmitted signal respectively in step S201, T c is a chip period; ⁇ position takes a value in the range of (0, T c ), which is represented in the chip Sampling position, in this embodiment, It is the power signal described in step S202.
  • step S6 Set a decision threshold ⁇ of the TOA estimation according to the rank R 1 (k) described in step S5. There are mainly the following steps:

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Noise Elimination (AREA)

Abstract

本发明公开了一种基于噪声消除的到达时间估计方法,包括下列步骤:S1、发射端发送超宽带脉冲序列;S2、对接收到的超宽带信号进行功率采样;S3、对功率采样序列求均值;S4、计算得到噪声均值向量;S5、采用秩和方法得到功率均值列向量的秩;S6、设置判决门限;S7、进行TOA估计。本发明提出的针对功率采样序列的均值操作,可以有效消除接收信号中的噪声,提高到达时间估计的精度。本发明采用秩和方法,用以鉴别超宽带脉冲信号和噪声信号,这使得鉴别过程更易操作,结果更准确可靠,并且可以有效去除离群值的影响。本发明采用的门限设置方法,形式简单,且可靠有效。

Description

一种基于噪声消除的到达时间估计方法 技术领域
本发明属于无线通信领域,涉及一种脉冲超宽带信号定位技术,具体涉及一种基于噪声消除的到达时间估计方法。
背景技术
脉冲超宽带信号具有时间分辨率极高、穿透能力强等特点,理论上,能提供厘米甚至是毫米级的测距和定位精度,并且发射时无需调制,系统复杂度低,因而在高精度定位技术中,得到广泛关注。到达时间(TOA)估计可以充分发挥脉冲超宽带技术的优势,具有较高的测距和定位精度,并且实现复杂度较低,是脉冲超宽带定位技术的常用方法。TOA估计的关键在于如何根据接收端信号,在多径信道中探测到第一路径(FP),即直达路径,消除接收端信号中的噪声干扰显得尤其重要。
在脉冲超宽带定位系统中,目前已经有大量的研究提出了各种关于TOA估计的方法,比如最大能量选择(MES)算法和跨越阈值(TC)算法。MES算法将最大能量块所在的时间作为TOA估计值。然而在实际情况下,第一路径往往不是能量最强路径,这使得MES算法性能欠佳。因此,许多方法是基于TC算法探测第一路径。TC算法将能量检测接收机的输出和一个固定阈值相比较,第一个跨越门限的能量块所在的时间作为TOA的估计值。但是这种算法需要一个经复杂设计得到的最优门限。在信道模型较复杂,信道先验信息未知的情况下,设置这样的最优门限非常困难。
公开号为CN103297087,公开日为2013年9月11日的发明专利“一种超宽带定位系统的到达时间估计方法”,提供了一种基于恒虚警率约束 的门限解算模型,虽然计算过程对能量序列进行了预先排序,减少了完成到达时间估计的计算量,但是该发明没有消除噪声干扰,并且所述方法中涉及一个用于解算出最优门限的迭代过程,时间复杂度高。公开号为CN106131949A,公开日为2016年11月16日的发明专利“一种基于能量均值检测的到达时间估计方法”提供了一种基于时间平均的最大最小能量均值来设置最优归一化门限,从而设置判决门限的方法,虽然利用多个脉冲进行时间平均降低了噪声对TOA估计的影响,但是该发明并不是主动式地消除噪声,效果有待提高。公开号为CN106879068A,公开日为2017年6月20日的发明专利“一种强多径环境下信号的到达时间估计方法”通过对接收信号的归一化滤波,降低了噪声干扰,同时减小了信号传输损失带来的影响,但是该发明只能抑制接收信号中的突发噪声。
综上所述,现有的TOA估计方法没有充分消除噪声影响,并且门限设置方法复杂,在实际情况下都有性能缺陷,高精度定位算法还有待提高。
发明内容
本发明的目的是为了解决现有技术中的上述缺陷,提供一种基于噪声消除的到达时间估计方法,通过对接受端信号进行去噪处理提高TOA估计精度。
本发明的目的可以通过采取如下技术方案达到:
一种基于噪声消除的到达时间估计方法,所述的到达时间估计方法包括以下步骤:
S1、发射端发送超宽带脉冲序列;
S2、接收到的超宽带信号r(t)通过低噪声放大器后进行带通滤波,然后通过平方律检波器,得到功率信号,再对该功率信号进行采样,得到接收信号的功率采样序列{A n,l,k},其中,A n,l,k表示对第n个符号里的第l帧中 的第k个码片得到的功率采样值,n=1,2,...,N s,l=1,2,...,N f,k=1,2,...,N c,N s表示发射信号的符号数,N f表示每个符号内的帧数,N c表示每帧内码片数;
S3、对所述的功率采样序列{A n,l,k}进行求均值操作以消除噪声,得到接收信号的功率均值矩阵V,其中V的第n行第k列元素V n,k
Figure PCTCN2018110448-appb-000001
确定,V的第k列元素所构成的功率均值列向量记作V k
S4、从所述的功率采样序列{A n,l,k}中抽取第1个码片构成噪声序列{A n,l,1},其中A n,l,1是A n,l,k在k=1时的取值,对{A n,l,1}求均值,得到噪声均值向量V ref,其中V ref的第n个元素
Figure PCTCN2018110448-appb-000002
Figure PCTCN2018110448-appb-000003
确定;
S5、对所述的功率均值列向量V k和所述的噪声均值向量V ref采用秩和方法,得到V k的秩R 1(k);
S6、根据所述的秩R 1(k)设置TOA估计的判决门限η;
S7、选取最先超越判决门限η的时间码片的
Figure PCTCN2018110448-appb-000004
位置处作为到达时间的估计值。
进一步地,所述的接收到的超宽带信号r(t)由
Figure PCTCN2018110448-appb-000005
其中,ω(t)是超宽带脉冲,脉冲宽度等于码片周期T c,T s、T f分别是发射信号的符号周期和帧周期,每一帧内,在超宽带脉冲所在位置前设置时间间隔τ guard作为保护间隔,n(t)表示均值为零、双边功率谱密度为
Figure PCTCN2018110448-appb-000006
的复加性高斯白噪声,
Figure PCTCN2018110448-appb-000007
是信道的单位冲激响应,其中α l和τ l分别是第l条路径的复衰减因子和延时,L为多径数,δ(t)是迪拉克δ函数。
进一步地,所述的功率采样序列A n,l,k
Figure PCTCN2018110448-appb-000008
确定,
其中T s、T f、T c分别是发射信号的符号周期、帧周期和码片周期,τ position在(0,T c)范围内取值,表示在码片内的采样位置,r bpf(t)是带通滤波器的输出,
Figure PCTCN2018110448-appb-000009
即为所述的通过平方律检波器后得到的功率信号。
进一步地,所述的秩和方法按照k的增序依次进行,其中k=1,2,...,N c,包括以下步骤:
S501、对每一个k,将V k和V ref中的元素放在一起,并对这些元素按幅值大小从小到大进行排序,构成有序序列W k。V k中的第n个元素V n,k在有序序列W k中的序号即为该元素的秩,记作
Figure PCTCN2018110448-appb-000010
S502、对每一个k,根据所述的
Figure PCTCN2018110448-appb-000011
得到列向量V k的秩R 1(k),其中R 1(k)通过式
Figure PCTCN2018110448-appb-000012
计算确定。
进一步地,所述的判决门限η的设置,包括以下步骤:
S601、所述的V k的秩R 1(k)按照k的增序构成行向量R 1=(R 1(1),R 1(2),...,R 1(N c)),将R 1标准正态化,记为Z,即
Figure PCTCN2018110448-appb-000013
S602、设置判决门限
Figure PCTCN2018110448-appb-000014
其中Z max为Z中元素的最大值。
进一步地,所述的选取时间码片,包括以下步骤:
S701、按照k的增序,将所述的Z中元素Z(k)与判决门限η依次比较;
S702、所述的向量Z中,最先超越判决门限η的元素记作Z(k 0),Z(k 0)所在的时间码片的
Figure PCTCN2018110448-appb-000015
位置处即为到达时间的估计值,元素Z(k 0)所在的时间码片的下标表示为k 0,即元素Z(k 0)所在的时间码片为第k 0个码片,则到达时间的估计值τ由
Figure PCTCN2018110448-appb-000016
计算确定。
本发明相对于现有技术具有如下的优点及效果:
1、本发明提出的针对功率采样序列的均值操作,可以有效消除接收信号中的噪声,提高到达时间估计的精度。而且这种噪声消除方法具有独立性,不依赖于信道先验信息的获取,适用于实际的超宽带定位系统。
2、本发明采用秩和方法,用以鉴别超宽带脉冲信号和噪声信号,而不是直接比较两者幅值大小。这使得鉴别过程更易操作,结果更准确可靠,并且可以有效去除离群值的影响。
3、本发明采用的门限设置方法,形式简单,且可靠有效。
附图说明
图1是本发明中公开的基于噪声消除的到达时间估计方法的流程图;
图2是本发明中接收端信号处理的流程图;
图3是本发明中发射的脉冲序列结构图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚,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。
实施例
本实施例公开了一种基于噪声消除的到达时间估计方法,如附图1和图2所示,该方法实现步骤如下:
S1、发射端发送如图3所示结构的超宽带脉冲序列。图3中,N s表示发射信号的符号数,N f表示每个符号内的帧数,N c表示每帧内码片数,相应的符号周期、帧周期、码片周期分别记作T s、T f、T c。本实施例中,设定具体参数如下:N s=30,N f=40,N c=200,T c=1ns,T f=N c×T c=200ns,T s=N f×T f=8000ns。
S2、接收到的超宽带信号r(t)通过低噪声放大器后进行带通滤波,然后通过平方律检波器,得到功率信号
Figure PCTCN2018110448-appb-000017
再对该功率信号进行采样,得到接收信号的功率采样序列{A n,l,k}。其中,A n,l,k表示对第n(n=1,2,...,N s)个符号里的第l(l=1,2,...,N f)帧中的第k(k=1,2,...,N c)个码片得到的功率采样值。具体包括以下步骤:
S201、接收到的超宽带信号r(t)通过低噪声放大器后,再通过带通滤波器,以去除带外噪声。接收到带噪声超宽带信号r(t)由
Figure PCTCN2018110448-appb-000018
确定。定义
Figure PCTCN2018110448-appb-000019
为发射的超宽带脉冲,脉冲宽度等于码片周期T c,其中θ=0.3×10 -9。每一帧内,在超宽带脉冲所在位置前设置时间间隔τ guard=80ns作为保护间隔。n(t)表示均值为零、双边功率谱密度为
Figure PCTCN2018110448-appb-000020
的复加性高斯白噪声,满足
Figure PCTCN2018110448-appb-000021
其中SNR表示信号噪声功率比(单位为dB),本实施例中,设定SNR取值范围为[0,30],单个超宽带脉冲的能量为E x=3.0051×10 -10J。h(t)是信道的单位冲激响应,本实施例中,考虑的信道模型是IEEE802.15.4a CM3的超宽带信道,信道的单位冲激响应为
Figure PCTCN2018110448-appb-000022
其中L为簇数,服从泊松分布,概率密度函数为
Figure PCTCN2018110448-appb-000023
定义第l簇内接收到的多径数目K=100;相位φ k,l是[0,2π]上均匀分布的随机变量;第l簇的时延T l满足泊松分布
Figure PCTCN2018110448-appb-000024
第k个多径成分相对于第l簇到达 时间T l的相对时延τ k,l满足混合泊松分布
Figure PCTCN2018110448-appb-000025
混合概率β=0.0184,路径到达速率λ 1=0.19ns -1,λ 2=2.97ns -1;第l簇中第k条路径的幅度衰减因子α k,l满足
Figure PCTCN2018110448-appb-000026
其中第一路径的衰减系数χ=0.86,功率延迟分布的增长速度γ rise=15.21,衰减系数γ 1=11.84。带通滤波器的输出记为r bpf(t)。
S202、经过带通滤波的接收信号通过平方律检波器,得到功率信号,功率信号记为
Figure PCTCN2018110448-appb-000027
S203、对功率信号进行采样,得到接收信号的功率采样序列{A n,l,k}。
其中,A n,l,k表示对第n(n=1,2,...,N s)个符号里的第l(l=1,2,...,N f)帧中的第k(k=1,2,...,N c)个码片得到的功率采样值。功率采样序列A n,l,k
Figure PCTCN2018110448-appb-000028
确定,其中T s、T f分别是步骤S201所述的发射信号的符号周期和帧周期,T c是码片周期;τ position在(0,T c)范围内取值,表示在码片内的采样位置,此实施例中,令
Figure PCTCN2018110448-appb-000029
是步骤S202所述的功率信号。
S3、对步骤S2所述的功率采样序列{A n,l,k}进行求均值操作,得到接收信号的功率均值矩阵V,其中V的第n(n=1,2,...,N s)行第k(k=1,2,...,N c)列元素V n,k
Figure PCTCN2018110448-appb-000030
确定。V的第k(k=1,2,...,N c)列元素所构成的功率均值列向量记作V k
S4、从步骤S2所述的功率采样序列{A n,l,k}中抽取第1个码片构成噪声序列{A n,l,1},其中A n,l,1是A n,l,k在k=1时的取值。对{A n,l,1}求均值,得到噪声均值向量V ref,其中V ref的第n(n=1,2,...,N s)个元素
Figure PCTCN2018110448-appb-000031
Figure PCTCN2018110448-appb-000032
确定。
S5、对步骤S3所述的功率均值列向量V k(k=1,2,...,N c)和步骤S4所述的噪声均值向量V ref采用秩和方法,得到V k的秩R 1(k),具体有以下步骤:
S501、对每一个k(k=1,2,...,N c),将V k和V ref中的元素放在一起,并对这些元素按幅值大小从小到大进行排序,构成有序序列W k。V k中的第n(n=1,2,...,N s)个元素V n,k在有序序列W k中的序号即为该元素的秩,记作
Figure PCTCN2018110448-appb-000033
Figure PCTCN2018110448-appb-000034
S502、对每一个k(k=1,2,...,N c),根据步骤S501中得到所述的
Figure PCTCN2018110448-appb-000035
得到列向量V k的秩R 1(k),其中R 1(k)通过式
Figure PCTCN2018110448-appb-000036
计算确定。
S6、根据步骤S5所述的秩R 1(k)设置TOA估计的判决门限η。主要有以下步骤:
S601、步骤S502中所述V k(k=1,2,...,N c)的秩R 1(k)按照k的增序构成行向量R 1=(R 1(1),R 1(2),...,R 1(N c)),将R 1标准正态化,记为Z,即
Figure PCTCN2018110448-appb-000037
S602、设置判决门限
Figure PCTCN2018110448-appb-000038
其中Z max为步骤S601所述Z中元素的最大值。
S7、TOA估计。按照k(k=1,2,...,N c)的增序,将步骤S601中的Z中元素Z(k)与判决门限η依次比较。假设最先超越判决门限η的元素为Z(k 0),其所在的时间码片的
Figure PCTCN2018110448-appb-000039
位置处作为到达时间的估计值。具体的,最先超越判决门限η的元素记作Z(k 0),元素Z(k 0)所在的时间码片的下标表示为k 0,则TOA的估计值τ由
Figure PCTCN2018110448-appb-000040
计算确定。
上述实施例为本发明较佳的实施方式,但本发明的实施方式并不受上述实施例的限制,其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化,均应为等效的置换方式,都包含在本发明的保护范围之内。

Claims (6)

  1. 一种基于噪声消除的到达时间估计方法,其特征在于,所述的到达时间估计方法包括以下步骤:
    S1、发射端发送超宽带脉冲序列;
    S2、接收到的超宽带信号r(t)通过低噪声放大器后进行带通滤波,然后通过平方律检波器,得到功率信号,再对该功率信号进行采样,得到接收信号的功率采样序列{A n,l,k},其中,A n,l,k表示对第n个符号里的第l帧中的第k个码片得到的功率采样值,n=1,2,...,N s,l=1,2,...,N f,k=1,2,...,N c,N s表示发射信号的符号数,N f表示每个符号内的帧数,N c表示每帧内码片数;
    S3、对所述的功率采样序列{A n,l,k}进行求均值操作以消除噪声,得到接收信号的功率均值矩阵V,其中V的第n行第k列元素V n,k
    Figure PCTCN2018110448-appb-100001
    确定,V的第k列元素所构成的功率均值列向量记作V k
    S4、从所述的功率采样序列{A n,l,k}中抽取第1个码片构成噪声序列{A n,l,1},其中A n,l,1是A n,l,k在k=1时的取值,对{A n,l,1}求均值,得到噪声均值向量V ref,其中V ref的第n个元素
    Figure PCTCN2018110448-appb-100002
    Figure PCTCN2018110448-appb-100003
    确定;
    S5、对所述的功率均值列向量V k和所述的噪声均值向量V ref采用秩和方法,得到V k的秩R 1(k);
    S6、根据所述的秩R 1(k)设置TOA估计的判决门限η;
    S7、选取最先超越判决门限η的时间码片的
    Figure PCTCN2018110448-appb-100004
    位置处作为到达时间的估计值。
  2. 根据权利要求1所述的一种基于噪声消除的到达时间估计方法, 其特征在于,所述的接收到的超宽带信号r(t)由
    Figure PCTCN2018110448-appb-100005
    确定,
    其中,ω(t)是超宽带脉冲,脉冲宽度等于码片周期T c,T s、T f分别是发射信号的符号周期和帧周期,每一帧内,在超宽带脉冲所在位置前设置时间间隔τ guard作为保护间隔,n(t)表示均值为零、双边功率谱密度为
    Figure PCTCN2018110448-appb-100006
    的复加性高斯白噪声,
    Figure PCTCN2018110448-appb-100007
    是信道的单位冲激响应,其中α l和τ l分别是第l条路径的复衰减因子和延时,L为多径数,δ(t)是迪拉克δ函数。
  3. 根据权利要求1所述的一种基于噪声消除的到达时间估计方法,其特征在于,所述的功率采样序列A n,l,k
    Figure PCTCN2018110448-appb-100008
    确定,
    其中T s、T f、T c分别是发射信号的符号周期、帧周期和码片周期,τ position在(0,T c)范围内取值,表示在码片内的采样位置,r bpf(t)是带通滤波器的输出,
    Figure PCTCN2018110448-appb-100009
    即为所述的通过平方律检波器后得到的功率信号。
  4. 根据权利要求1所述的一种基于噪声消除的到达时间估计方法,其特征在于,所述的秩和方法按照k的增序依次进行,其中k=1,2,...,N c,包括以下步骤:
    S501、对每一个k,将V k和V ref中的元素放在一起,并对这些元素按幅值大小从小到大进行排序,构成有序序列W k。V k中的第n个元素V n,k在有序序列W k中的序号即为该元素的秩,记作
    Figure PCTCN2018110448-appb-100010
    S502、对每一个k,根据所述的
    Figure PCTCN2018110448-appb-100011
    得到列向量V k的秩R 1(k),其中R 1(k)通过式
    Figure PCTCN2018110448-appb-100012
    k=1,2,...,N c计算确定。
  5. 根据权利要求1所述的一种基于噪声消除的到达时间估计方法,其特征在于,所述的判决门限η的设置,包括以下步骤:
    S601、所述的V k的秩R 1(k)按照k的增序构成行向量R 1=(R 1(1),R 1(2),...,R 1(N c)),将R 1标准正态化,记为Z,即
    Figure PCTCN2018110448-appb-100013
    S602、设置判决门限
    Figure PCTCN2018110448-appb-100014
    其中Z max为Z中元素的最大值。
  6. 根据权利要求1所述的一种基于噪声消除的到达时间估计方法,其特征在于,所述的选取时间码片,包括以下步骤:
    S701、按照k的增序,将所述的Z中元素Z(k)与判决门限η依次比较;
    S702、所述的向量Z中,最先超越判决门限η的元素记作Z(k 0),Z(k 0)所在的时间码片的
    Figure PCTCN2018110448-appb-100015
    位置处即为到达时间的估计值,元素Z(k 0)所在的时间码片的下标表示为k 0,即元素Z(k 0)所在的时间码片为第k 0个码片,则到达时间的估计值τ由
    Figure PCTCN2018110448-appb-100016
    计算确定。
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