CN114205904B - Ultra-wideband signal arrival time estimation method based on soft information sequence detection - Google Patents

Ultra-wideband signal arrival time estimation method based on soft information sequence detection Download PDF

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CN114205904B
CN114205904B CN202111507909.2A CN202111507909A CN114205904B CN 114205904 B CN114205904 B CN 114205904B CN 202111507909 A CN202111507909 A CN 202111507909A CN 114205904 B CN114205904 B CN 114205904B
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CN114205904A (en
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张霆廷
刘凡
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Shenzhen Graduate School Harbin Institute of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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Abstract

The invention provides an ultra-wideband signal arrival time estimation method based on soft information sequence detection, which realizes the design of a clock asynchronous communication positioning integrated system based on pulse ultra-wideband signals, and comprises the following steps of
Figure DEST_PATH_BDA0003403971480000011
Each of the anchor node, the 1 target node with unknown position and the 1 central node with synchronous clock, the set of the anchor node and the target node position are respectively expressed as
Figure 406246DEST_PATH_BDA0003403971480000011
And
Figure DEST_PATH_BDA0003403971480000012
and the anchor node receives ICL IR-UWB signals broadcast and transmitted by the target node, respectively carries out data demodulation and TOA estimation, and finally the central node carries out target position estimation according to the TOA of each anchor node. The beneficial effects of the invention are as follows: the invention can realize the communication and positioning of the wireless system under the condition that the clocks of the receiving and transmitting ends are asynchronous, and the receiving and transmitting ends do not need to call back the clock synchronization, thus reducing the complexity of the algorithm and the hardware cost; aiming at demodulation and positioning errors caused by unreliable pulse detection, the invention provides a solution based on soft information and shows good positioning and communication performance.

Description

Ultra-wideband signal arrival time estimation method based on soft information sequence detection
Technical Field
The invention relates to the field of communication and positioning navigation, in particular to an ultra-wideband signal arrival time estimation method and a clock asynchronous communication positioning integrated system based on a pulse ultra-wideband signal.
Background
In modern communication systems, reliable data transmission and high-precision positioning are increasingly in demand for services. The pulse ultra wideband (IR-UWB) signal has Wide application in the fields of wireless communication, sensing, detection, positioning, etc. due to the characteristic advantages of high time resolution, large Bandwidth, etc. Meanwhile, in order to improve the frequency spectrum and the hardware utilization efficiency, the design of the integrated communication and positioning (Integration of Communication and Localization, ICL) system becomes a research hot spot of the wireless communication system.
In recent years, there has been a great deal of research devoted to accurate ultra wideband TOA estimation algorithms in complex environments. The most commonly used is a two-step TOA estimation strategy, wherein the first step is to perform rough pulse capturing at the receiving end, and the second step is to perform more accurate TOA estimation through various algorithms within the range of the first step of pulse capturing. In recent years, the wireless positioning field proposes a Soft Information (SI) concept, and Soft Information ranging can provide more abundant pulse Information compared with conventional single-value distance estimation, and particularly shows good ranging and positioning performance in a complex communication environment.
Communication and positioning systems based on ultra wideband technology are well established in commercial applications. However, most schemes communicate and locate separately, with the communication and location algorithms operating in different time slots or frequency bands. In addition, high-precision clock synchronization is also difficult to achieve in practical systems. Most current studies assume network clock synchronization, which also limits its use in practical systems.
Disclosure of Invention
The invention provides an ultra-wideband signal arrival time estimation method based on soft information sequence detection, which comprises N b Each of the anchor node, the 1 target node with unknown position and the 1 central node with synchronous clock, the set of the anchor node and the target node position are respectively expressed as
Figure BDA0003403971480000011
and />
Figure BDA0003403971480000012
The anchor node receives ICL IR-UWB signals broadcast and transmitted by the target node, respectively carries out data demodulation and TOA estimation, and finally the center node carries out target position estimation according to the TOA of each anchor node;
the positions of the target node and the anchor node are denoted as p= [ p ], respectively x ,p y ,p z T and rm ＝x m ,y m ,z m T ，
Figure BDA0003403971480000013
The true TOA value from the target node to the mth anchor node is expressed as:
Figure BDA0003403971480000021
where c is the propagation velocity of an electromagnetic wave in air, I.I 2 Representing a 2-norm.
As a further development of the invention, the IR-UWB transmission signal is in the form of:
Figure BDA0003403971480000022
wherein ,Tf Representing pulse repetition interval, w t representing an energy normalized second order Gaussian pulse, N f Represents the total pulse number, delta represents the pulse position modulation length, q j Represents the j-th data transmitted by the system, which is 0 or 1, E tb Representing the energy of transmitting one bit of data, E tb ＝T f P t ，P t Representing the signal transmission power;
the received signal at the mth anchor node is in the form of:
Figure BDA0003403971480000023
where represents a linear convolution, the initial clock offset between the anchor node and the target node is deltat,
Figure BDA0003403971480000024
for the transmission delay of the pulse signal from the target to the mth anchor node, h t is a UWB small-scale fading channel, and each parameter needs to satisfy the following conditions:
δ+t s ＜T f ,δ-t s ＞0
wherein ,ts Representing the maximum delay spread of the UWB channel.
As a further improvement of the present invention, the pulse arrival time of the j-th pulse of the m-th anchor node is:
Figure BDA0003403971480000025
as a further improvement of the present invention, definition
Figure BDA0003403971480000026
The arrival time interval for an anchor adjacent pulse:
Figure BDA0003403971480000027
wherein ,
Figure BDA0003403971480000028
representing an estimation error, then +.>
Figure BDA0003403971480000029
and />
Figure BDA00034039714800000210
The current data can be demodulated:
Figure BDA00034039714800000211
while the data demodulation function f can be expressed as a sequence estimation problem.
As a further improvement of the present invention, the pseudo arrival time of the jth frame data of the mth anchor node is defined as:
Figure BDA0003403971480000031
the location of the target node may be expressed as:
Figure BDA00034039714800000315
wherein g p = ||β j -Δt-t d ||，
Figure BDA0003403971480000032
Δt＝IΔt，/>
Figure BDA0003403971480000033
Figure BDA0003403971480000034
Due to beta j There is an estimation error and therefore a numerical algorithm Jie Suanshang is used to describe the equation.
As a further refinement of the invention, the numerical algorithm comprises a linear least squares or maximum likelihood algorithm.
As a further improvement of the present invention, the TOA estimation is performed by using a matched filtering algorithm based on pulse recognition, the signal and noise within one pulse repetition interval are discretized into r n and z n, and the transmitted signal is transmitted
Figure BDA0003403971480000035
As local template signals, m and j are omitted for simplicity of expression:
Figure BDA0003403971480000036
the decision variables of the matched filtering are:
Figure BDA0003403971480000037
wherein ,Ns Counting the number of samples within one pulse repetition interval; r is then MF The expectations and variances of (1) are as follows:
Figure BDA0003403971480000038
Figure BDA0003403971480000039
wherein ,
Figure BDA00034039714800000310
representing the variance of the noise; establishing a hypothesis testing model through the decision variables of the matched filtering:
H 0 :
Figure BDA00034039714800000311
H 1 :
Figure BDA00034039714800000312
H 0 and H1 Representing the situation of only noise in one pulse and a pulse signal respectively;
μ 0 ＝0,
Figure BDA00034039714800000313
Figure BDA00034039714800000314
the impulse false alarm probability (False Alarm Probability, FAP) is expressed as:
Figure BDA0003403971480000041
wherein Q represents the right tail function Q function of standard normal distribution; according to the constant false alarm detection criterion, a threshold value of pulse detection is obtained:
Figure BDA0003403971480000042
as a further improvement of the present invention, the pulse detection threshold may be calculated by the preset FAP, and the pulse detection scheme in one PRI may be divided into the following cases:
case 1: if there is only one decision r MF > γ, consider that there is only one pulse within the current PRI;
case 2: if there are two or more decision variables r in a PRI MF If the amplitude of the pulse is larger than the threshold value gamma, sequencing from large to small according to the amplitude of the pulse at each sampling point; judging from the second maximum pulse, if the interval between one pulse and the maximum pulse is larger than the channel coherence time, considering that two signal pulses exist in the current PRI, otherwise, considering that only one signal pulse is needed, namely the amplitude maximum pulse;
case 3: if none of the decision variables exceeds the threshold, then the current PRI is deemed to have no signal pulses.
As a further improvement of the invention, soft information based on the received pulse amplitude is defined as follows:
Figure BDA0003403971480000043
when r is MF At the time of > gamma-ray,
Figure BDA00034039714800000410
the larger the current pulse, the more reliable it is; when r is MF When < gamma->
Figure BDA00034039714800000411
The larger the current pulse, the less reliable the representation;
definition of the definition
Figure BDA0003403971480000044
For soft information based on adjacent pulse intervals, +.>
Figure BDA0003403971480000045
Obeying gaussian distribution, defined as:
Figure BDA0003403971480000046
assuming that the probabilities of transmitting data '0' and '1' are equal, therefore
Figure BDA0003403971480000047
Can be expressed as: />
Figure BDA0003403971480000048
wherein
Figure BDA0003403971480000049
As a further improvement of the present invention,
Figure BDA0003403971480000051
and />
Figure BDA0003403971480000052
Representing high confidence and low confidence intervals,
if it is
Figure BDA0003403971480000053
Only one pulse exists in the interval, and the current pulse signal is reserved;
if the current pulse is located
Figure BDA0003403971480000054
If the interval between adjacent pulses is smaller, the current pulse signal is considered unreliable and the confidence coefficient of the next pulse is calculated continuously; if the adjacent pulses are spaced apart a greater distance, then a missing pulse is considered to be present before that, then
Figure BDA0003403971480000055
Selecting the pulse with the largest amplitude in the interval as a missing detection pulse;
if at
Figure BDA0003403971480000056
There are two pulses in it, the pulse with larger amplitude is chosen as the credible pulse, the other is considered asAnd false alarm pulse.
The beneficial effects of the invention are as follows: the invention can realize the communication and positioning of the wireless system under the condition that the clocks of the receiving and transmitting ends are asynchronous, and the receiving and transmitting ends do not need to call back the clock synchronization, thus reducing the complexity of the algorithm and the hardware cost; aiming at demodulation and positioning errors caused by unreliable pulse detection, the invention provides a solution based on soft information and shows good positioning and communication performance.
Drawings
FIG. 1 is a schematic diagram of a networking architecture of the present invention;
FIG. 2 is a schematic diagram of an integrated algorithm for clock asynchronous communication and positioning according to the present invention;
FIG. 3 is a schematic diagram of a frame structure of the present invention;
fig. 4 is a schematic diagram of soft information based sequence estimation of the present invention.
Detailed Description
The invention discloses an ultra-wideband signal arrival time estimation method based on soft information sequence detection, which realizes a clock asynchronous communication positioning integrated system based on pulse ultra-wideband signals.
The invention has two main innovation points: firstly, a low-complexity sequence estimation demodulation scheme is provided, and the scheme can obtain data symbols and target positions at the same time, so that a theoretical basis is provided for realizing communication positioning integration; secondly, aiming at serious errors caused by unreliable detection and judgment of a receiving end of a clock asynchronous system, a solution based on Soft Information (SI) is provided, the phenomenon of pulse dislocation in the data demodulation process is avoided, and good communication and positioning performance is obtained.
The basic idea and main operation of the invention are described below:
as shown in fig. 1, N is set in a centralized ad hoc network (system network structure) b Anchor node with synchronous clock, 1 target node with unknown position and method for producing the same1 master station (central node). The set of anchor node and target node locations are represented as
Figure BDA0003403971480000057
and />
Figure BDA0003403971480000058
The anchor node receives the ICL IR-UWB signal broadcast from the target node and performs data demodulation and TOA estimation, respectively. And finally, the central node carries out target position estimation according to TOAs of the anchor points. />
The positions of the target node and the anchor node are denoted as p= [ p ], respectively x ,p y ,p z T and rm ＝x m ,y m ,z m T ，
Figure BDA0003403971480000061
The true TOA value from the target node to the mth anchor node is expressed as:
Figure BDA0003403971480000062
where c is the propagation velocity of an electromagnetic wave in air, I.I 2 Representing a 2-norm.
The form of the (signal model) IR-UWB transmit signal is:
Figure BDA0003403971480000063
wherein ,Tf Representing pulse repetition intervals (Pulse Repetition Interval, PRI), w t represents an energy normalized second order Gaussian pulse, N f Represents the total pulse number, delta represents the pulse position modulation (Pulse Position Modulation, PPM) length, q j Represents the j-th data transmitted by the system, which is 0 or 1, E tb Representing the energy of transmitting one bit of data, E tb ＝T f P t ，P t Representing the signal transmit power.
The received signal at the mth anchor node is in the form of:
Figure BDA0003403971480000064
where represents a linear convolution, the initial clock offset between the anchor node and the target node is deltat,
Figure BDA0003403971480000065
for the transmission delay of the pulse signal from the target to the mth anchor point, h t is a UWB small-scale fading channel, and the noise of the receiving end of the system is set to be additive white gaussian noise (Additive White Gaussian Noise, AWGN). To avoid severe intersymbol interference, the following conditions are satisfied for each parameter:
δ+t s ＜T f ,δ-t s ＞0
wherein ,ts Representing the maximum delay spread of the UWB channel.
(communication positioning integration algorithm)
The pulse arrival time of the j-th pulse of the m-th anchor node is:
Figure BDA0003403971480000066
therefore, the main work of the invention is to solve t at the same time d and qj 。
(1) Sequence detection and data demodulation
We define
Figure BDA0003403971480000067
The arrival time interval of adjacent pulses for an anchor node:
Figure BDA0003403971480000068
wherein ,
Figure BDA0003403971480000069
representation ofAnd estimating an error. Then according to the previous estimation data +.>
Figure BDA00034039714800000610
and />
Figure BDA00034039714800000611
The current data can be demodulated:
Figure BDA0003403971480000071
while the data demodulation function f can be expressed as a sequence estimation problem:
Figure BDA0003403971480000072
(2) Clock asynchronous positioning
Defining a pseudo-arrival time (pseudo-TOA) of the mth anchor node jth frame data as:
Figure BDA0003403971480000073
the location of the target node may be expressed as:
Figure BDA0003403971480000074
wherein g p = ||β j -Δt-t d ||，
Figure BDA0003403971480000075
Δt＝IΔt，/>
Figure BDA0003403971480000076
Figure BDA0003403971480000077
Due to beta j There is an estimation error and thus numerical algorithms such as linear least squares can be employed(Linear Least Square, LLS) or maximum likelihood (Maximum Likelihood, ML) to solve the above equation.
A block diagram of the communication positioning integrated algorithm is shown in fig. 2.
(pulse identification) due to TOA estimation
Figure BDA0003403971480000078
The invention is a key parameter to be solved, and a Matched-Filtering (MF) algorithm based on pulse identification is adopted to carry out TOA estimation. The signal and noise within one pulse repetition interval are discretized into r n and z n, the signal is transmitted +.>
Figure BDA0003403971480000079
As local template signals, m and j are omitted here for simplicity of expression:
Figure BDA00034039714800000710
the decision variables of the matched filtering are:
Figure BDA00034039714800000711
wherein ,Ns The number of samples within one pulse repetition interval. R is then MF The expectations and variances of (1) are as follows:
Figure BDA00034039714800000712
Figure BDA0003403971480000081
wherein ,
Figure BDA0003403971480000082
representing the variance of the noise. We build a hypothesis testing model by matching filtered decision variables:
H 0 :
Figure BDA0003403971480000083
Figure BDA0003403971480000084
Figure BDA0003403971480000085
H 0 and H1 Representing the case of only noise within one pulse and by one pulse signal, respectively.
μ 0 ＝0,
Figure BDA0003403971480000086
Figure BDA0003403971480000087
The impulse false alarm probability (False Alarm Probability, FAP) is expressed as:
Figure BDA0003403971480000088
wherein Q represents the right tail function Q function of the standard normal distribution. According to the constant false alarm detection criterion, we can get the threshold value of pulse detection:
Figure BDA0003403971480000089
the pulse detection threshold value can be calculated through the preset FAP, and the pulse detection scheme in one PRI can be divided into the following cases:
if there is only one decision r MF > γ, consider that there is only one pulse within the current PRI;
if there are two or more decisions within one PRIVariable r MF When the amplitude of the pulse is larger than the threshold value gamma, the amplitude of the pulse is ordered from large to small according to each sampling point. Starting from the second largest pulse, if there is a gap between one pulse and the largest pulse that is greater than the channel coherence time, we consider that there are two signal pulses present in the current PRI, otherwise we consider that there is only one signal pulse, i.e., the amplitude largest pulse.
If no decision variable exceeds the threshold, then the current PRI is considered to have no signal pulses.
(pulse detection enhancement) according to CFAR criteria, the pulse detection probability can be expressed as:
Figure BDA0003403971480000091
in the sequence detection process, the detection of the pulse train head is of great importance, and the pulse detection probability is increased by a method of increasing the transmission power of the first two pulses. The communication frame structure is shown in fig. 3.
In a clock asynchronous detection system (based on soft information detection enhancement), false alarms or missed detection of pulses can cause misplacement of the pulse trains, thereby having serious influence on demodulation of communication data and estimation of TOA. We build likelihood functions based on the concept of Soft Information (SI) to determine the confidence level of the current pulse.
It can be seen intuitively that the larger the range of MF decision variables beyond the threshold, the more reliable the current pulse, so we define soft information (Soft Amplitude Information, SAI) based on the received pulse amplitude as follows:
Figure BDA0003403971480000092
when r is MF At the time of > gamma-ray,
Figure BDA0003403971480000093
the larger the current pulse, the more reliable it is; when r is MF When < gamma->
Figure BDA0003403971480000094
The larger the current pulse, the less reliable the representation. />
Similarly, we define
Figure BDA0003403971480000095
For soft information (Soft Interval Information) based on adjacent pulse intervals, and>
Figure BDA0003403971480000096
obeying gaussian distribution, we define:
Figure BDA0003403971480000097
assuming that the probabilities of transmitting data '0' and '1' are equal, therefore
Figure BDA0003403971480000098
Can be expressed as:
Figure BDA0003403971480000099
wherein
Figure BDA00034039714800000910
Fig. 4 is a schematic diagram of sequence estimation based on soft information, with alphabetic paths being paths selected for demodulation sequences.
Figure BDA00034039714800000911
and />
Figure BDA00034039714800000912
Representing high confidence and low confidence intervals.
If (if)
Figure BDA00034039714800000913
Only one pulse exists in the interval, and the current pulse signal, such as a path a, is reserved;
if the current pulse is located
Figure BDA0003403971480000101
If the interval between adjacent pulses is smaller, we consider that the current pulse signal is unreliable and continue to calculate the confidence of the next pulse or reacquire the pulse (missed pulse) in the high confidence interval, such as paths b and d;
if the adjacent pulse interval is large, we consider that there is a missing pulse before this, we are then
Figure BDA0003403971480000103
And selecting the pulse with the largest amplitude in the interval as the missing detection pulse.
If at
Figure BDA0003403971480000102
There are two pulses in the pulse, and one pulse with larger amplitude is selected as a trusted pulse, and the other pulse is considered as a false alarm pulse, such as paths e and f.
The beneficial effects of the invention are as follows:
1. the invention can realize the communication and positioning of the wireless system under the condition that the clocks of the receiving and transmitting ends are asynchronous, and the receiving and transmitting ends do not need to call back the clock synchronization, thus reducing the complexity of the algorithm and the hardware cost.
2. Aiming at demodulation and positioning errors caused by unreliable pulse detection, the invention provides a solution based on soft information and shows good positioning and communication performance.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.

Claims (10)

1. Ultra-wideband signal arrival based on soft information sequence detectionThe time estimation method is characterized in that: comprising N b Each of the anchor node, the 1 target node with unknown position and the 1 central node with synchronous clock, the set of the anchor node and the target node position are respectively expressed as
Figure FDA0003403971470000011
and />
Figure FDA0003403971470000012
The anchor node receives ICL IR-UWB signals broadcast and transmitted by the target node, respectively carries out data demodulation and TOA estimation, and finally the center node carries out target position estimation according to the TOA of each anchor node;
the positions of the target node and the anchor node are denoted as p= [ p ], respectively x ,p y ,p z ] T and rm ＝x m ,y m ,z m T ，
Figure FDA0003403971470000013
The true TOA value from the target node to the mth anchor node is expressed as:
Figure FDA0003403971470000014
where c is the propagation velocity of an electromagnetic wave in air, I.I 2 Representing a 2-norm.
2. The ultra-wideband signal arrival time estimation method according to claim 1, wherein: the IR-UWB transmission signal is in the form of:
Figure FDA0003403971470000015
wherein ,Tf Representing pulse repetition interval, wt represents energy normalized second order Gaussian pulse, N f Represents the total pulse number, delta represents the pulse position modulation length, q j Represents the j-th data transmitted by the system, which is 0 or 1, E tb Representing the energy of transmitting one bit of data, E tb ＝T f P t ，P t Representing the signal transmission power;
the received signal at the mth anchor node is in the form of:
Figure FDA0003403971470000016
where represents a linear convolution, the initial clock offset between the anchor node and the target node is deltat,
Figure FDA0003403971470000017
for the transmission delay of the pulse signal from the target to the mth anchor node, ht is a UWB small-scale fading channel, and each parameter needs to satisfy the following conditions:
δ+t s ＜T f ,δ-t s ＞0
wherein ,ts Representing the maximum delay spread of the UWB channel.
3. The ultra-wideband signal arrival time estimation method according to claim 2, wherein: the pulse arrival time of the j-th pulse of the m-th anchor node is:
Figure FDA0003403971470000018
4. the ultra-wideband signal arrival time estimation method according to claim 3, wherein: definition of the definition
Figure FDA0003403971470000021
The arrival time interval for an anchor adjacent pulse:
Figure FDA0003403971470000022
wherein ,
Figure FDA0003403971470000023
Figure FDA0003403971470000024
representing an estimation error, then +.>
Figure FDA0003403971470000025
and />
Figure FDA0003403971470000026
The current data can be demodulated:
Figure FDA0003403971470000027
while the data demodulation function f can be expressed as a sequence estimation problem.
5. The ultra-wideband signal arrival time estimation method according to claim 4, wherein: defining the pseudo arrival time of the jth frame data of the mth anchor node as follows:
Figure FDA0003403971470000028
/>
the location of the target node may be expressed as:
Figure FDA0003403971470000029
wherein gp= |β j -Δt-t d ||，
Figure FDA00034039714700000210
Δt＝IΔt，/>
Figure FDA00034039714700000211
Figure FDA00034039714700000212
Due to beta j There is an estimation error and therefore a numerical algorithm Jie Suanshang is used to describe the equation.
6. The ultra-wideband signal arrival time estimation method according to claim 5, wherein: the numerical algorithm includes a linear least squares or maximum likelihood algorithm.
7. The ultra-wideband signal arrival time estimation method according to claim 5, wherein: TOA estimation is carried out by adopting a matched filtering algorithm based on pulse identification, signals and noise in a pulse repetition interval are discretized into rn and zn, and a transmitting signal is transmitted
Figure FDA00034039714700000213
As local template signals, m and j are omitted for simplicity of expression:
Figure FDA00034039714700000214
the decision variables of the matched filtering are:
Figure FDA00034039714700000215
wherein ,Ns Counting the number of samples within one pulse repetition interval; r is then MF The expectations and variances of (1) are as follows:
Figure FDA00034039714700000216
Figure FDA0003403971470000031
wherein ,
Figure FDA0003403971470000032
representing the variance of the noise; establishing a hypothesis testing model through the decision variables of the matched filtering:
H 0 :
Figure FDA0003403971470000033
H 1 :
Figure FDA0003403971470000034
H 0 and H1 Representing the situation of only noise in one pulse and a pulse signal respectively;
μ 0 ＝0,
Figure FDA0003403971470000035
Figure FDA0003403971470000036
the impulse false alarm probability (False Alarm Probability, FAP) is expressed as:
P FA ＝PH 1 :
Figure FDA0003403971470000037
wherein Q represents the right tail function Q function of standard normal distribution; according to the constant false alarm detection criterion, a threshold value of pulse detection is obtained:
Figure FDA0003403971470000038
8. the ultra-wideband signal arrival time estimation method according to claim 7, wherein: the pulse detection threshold can be calculated through the preset FAP, and the pulse detection scheme in one PRI is divided into the following cases:
case 1: if there is only one decision r MF > γ, consider that there is only one pulse within the current PRI;
case 2: if there are two or more decision variables r in a PRI MF If the amplitude of the pulse is larger than the threshold value gamma, sequencing from large to small according to the amplitude of the pulse at each sampling point; judging from the second maximum pulse, if the interval between one pulse and the maximum pulse is larger than the channel coherence time, considering that two signal pulses exist in the current PRI, otherwise, considering that only one signal pulse is needed, namely the amplitude maximum pulse;
case 3: if none of the decision variables exceeds the threshold, then the current PRI is deemed to have no signal pulses.
9. The ultra-wideband signal arrival time estimation method according to any one of claims 1 to 8, wherein: soft information based on the received pulse amplitude is defined as follows:
Figure FDA0003403971470000039
when r is MF At the time of > gamma-ray,
Figure FDA0003403971470000041
the larger the current pulse, the more reliable it is; when r is MF When < gamma->
Figure FDA0003403971470000042
The larger the current pulse, the less reliable the representation;
definition of the definition
Figure FDA0003403971470000043
For soft information based on adjacent pulse intervals, +.>
Figure FDA0003403971470000044
Obeying gaussian distribution, defined as:
Figure FDA0003403971470000045
assuming that the probabilities of transmitting data '0' and '1' are equal, therefore
Figure FDA0003403971470000046
Can be expressed as:
Figure FDA0003403971470000047
wherein
Figure FDA0003403971470000048
10. The ultra-wideband signal arrival time estimation method according to claim 9, wherein:
Figure FDA0003403971470000049
and />
Figure FDA00034039714700000410
Representing high confidence and low confidence intervals,
if it is
Figure FDA00034039714700000411
Only one pulse exists in the interval, and the current pulse signal is reserved;
if the current pulse is located
Figure FDA00034039714700000412
If the interval between adjacent pulses is smaller, the current pulse signal is considered unreliable and the confidence coefficient of the next pulse is calculated continuously; if the adjacent pulses have a larger spacing, it is assumed that there is a missing pulse before this, then at +.>
Figure FDA00034039714700000413
Selecting the pulse with the largest amplitude in the interval as a missing detection pulse;
if at
Figure FDA00034039714700000414
There are two pulses in the pulse, the pulse with larger amplitude is selected as the credible pulse, and the other pulse is regarded as the false alarm pulse. />
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