CN114609652A - A multi-frequency open-loop receiver tracking method and system under extreme ionospheric anomalies - Google Patents

Abstract

The invention provides a multi-frequency open-loop receiver tracking method and a multi-frequency open-loop receiver tracking system under extreme ionosphere anomaly, which belong to the field of navigation satellite positioning, and comprise the following steps: receiving navigation signals of each Beidou satellite in real time; determining the transmission time of the navigation signal from the satellite to the receiver at the current moment, determining the Doppler frequency of the navigation signal, and erasing the carrier wave of the navigation signal; adopting network enhancement system information to erase the navigation information of the carrier erasing signal; dividing the navigation erasing signal into a plurality of signal blocks according to the spread spectrum code period of the navigation signal, and performing coherent accumulation on the plurality of signal blocks to obtain an accumulated signal; erasing the spread spectrum codes of the accumulated signals to obtain complex signals; optimizing a state space formula of the Kalman filter based on a multi-frequency ionosphere scintillation model; and filtering the complex signal by adopting an optimized Kalman filter to obtain a tracking signal at the current moment. The positioning accuracy can be improved under the condition of the abnormality of the strong ionization layer.

Description

A multi-frequency open-loop receiver tracking method and system under extreme ionospheric anomalies

technical field

The invention relates to the field of navigation satellite positioning, in particular to a multi-frequency open-loop receiver tracking method and system under extreme ionospheric anomalies.

Background technique

The ionosphere is one of the largest sources of positioning errors in the Global Navigation Satellite System (GNSS). Under ionospheric anomalies, the integrity, accuracy, and availability of GNSS systems can be severely affected. In particular, small-scale time-varying plasma irregularities in the ionosphere cause rapid, random fluctuations in the amplitude and phase of GNSS signals, a phenomenon known as ionospheric scintillation. The occurrence of scintillation is affected by local time, season, latitude, and solar and geomagnetic activity. Studies have shown that the scintillation concentration occurs in the equatorial extension zone of ±20° north and south of the geomagnetic equator and the high latitude regions of 65° to 90° north and south of the geomagnetic equator.

GNSS receivers require stable, continuous tracking of satellite signals in order to calculate the distance the signal travels from the satellite to the receiver as accurately as possible. The receiver tracks the carrier of the received signal through a PLL (Phase Locked Loop, phase-locked loop), and strips the carrier component in the signal. At the same time, the code phase is tracked by the code loop to obtain an accurate code phase. When ionospheric scintillation occurs, the tracking performance of the receiver carrier loop and code loop decreases, the phase and code tracking errors increase, and the noise of the GNSS carrier and pseudorange observations increases. Under strong ionospheric anomalies, the tracking loop of GNSS receivers will experience frequent cycle slips and lose lock, which poses a major threat to the application of GNSS. If satellite coverage is poor to begin with, the user's location availability may become unreliable in the event of flickering. Even with good satellite coverage, strong scintillation affecting multiple satellites can still disrupt the availability of location services. Distance measurement errors due to these issues can be 3 to 10 times larger. With the large number of applications of GNSS in projects that have strict requirements on the accuracy, precision and reliability of position estimation, the performance requirements for precise positioning are also increasing, so it is necessary to suppress the impact of flicker on GNSS.

Strong ionospheric scintillation usually leads to the phenomenon of deep fading of signal amplitude and rapid phase jitter at the same time, causing frequent loss of lock and cycle slip of the receiver, which brings serious problems to the application of precision navigation and positioning and applications with strict life safety requirements. threaten. The traditional GNSS tracking loop usually adopts the closed-loop tracking algorithm based on proportional integral filter or Kalman filter (KF). This in turn affects the performance of the algorithm and affects the accuracy of positioning.

In addition, in the prior art, there is also a strategy of using an open-loop architecture to cope with the influence of strong flicker. Although the open-loop tracking loop will not lose lock, the measurement accuracy is poor. Therefore, how to balance the requirements of coping with loss of lock and ensuring positioning accuracy has become an urgent problem to be solved.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a multi-frequency open-loop receiver tracking method and system under extreme ionospheric anomalies, which can improve positioning accuracy under strong ionospheric anomalies.

For achieving the above object, the present invention provides the following scheme:

A multi-frequency open-loop receiver tracking method under extreme ionospheric anomalies, comprising:

Real-time reception of navigation signals from various Beidou satellites;

For the navigation signal of any Beidou satellite, according to the position of the Beidou satellite at the previous moment and the position of the receiver, determine the transmission time of the navigation signal from the Beidou satellite to the receiver at the current moment; the position and navigation of the Beidou satellite at the initial moment The transmission time of the signal is predetermined;

determining the Doppler frequency of the navigation signal according to the transmission time;

According to the Doppler frequency, the carrier of the navigation signal is erased to obtain a carrier erased signal;

Using network enhancement system information, the navigation information of the carrier erasure signal is erased to obtain a navigation erasure signal;

According to the spreading code period of the navigation signal, the navigation erasure signal is divided into multiple signal blocks, and the multiple signal blocks are coherently accumulated to obtain an accumulated signal;

Erasing the spreading code of the accumulated signal to obtain a complex signal;

Based on the multi-frequency ionospheric scintillation model, the state space formula of the Kalman filter is optimized to obtain the optimized Kalman filter; The amplitude and phase of the ionospheric scintillation component are modeled on the sample signal transmitted on the ionosphere;

The complex signal is filtered by the optimized Kalman filter to obtain the tracking signal at the current moment.

Optionally, the determining the Doppler frequency of the navigation signal according to the transmission time specifically includes:

According to the transmission time, determine the running speed of the Beidou satellite at the current moment;

The Doppler frequency of the navigation signal is determined according to the running speed of the Beidou satellite at the current moment.

Optionally, the following formula is used to determine the Doppler frequency of the Beidou satellite navigation signal:

为导航信号的多普勒频率，I为接收机到北斗卫星的单位方向矢量，V^SV为当前时刻北斗卫星的运行速度，

为接收机时钟频率偏移估计。in,

is the Doppler frequency of the navigation signal, I is the unit direction vector from the receiver to the Beidou satellite, V ^SV is the running speed of the Beidou satellite at the current moment,

is an estimate of the receiver clock frequency offset.

Optionally, according to the Doppler frequency, the carrier of the navigation signal is erased to obtain a carrier erased signal, which specifically includes:

determining a Doppler shift of the navigation signal according to the Doppler frequency;

determining the carrier of the navigation signal according to the Doppler shift;

The carrier wave of the navigation signal is erased to obtain a carrier wave erase signal.

Optionally, the following formula is used to coherently accumulate multiple signal blocks to obtain an accumulated signal:

Among them, w[n] is the accumulated signal, L is the number of spreading code cycles, z[n+kN] is the kN-th signal block, N is the number of samples in each signal block, and n represents the discrete signal.

Optionally, erasing the spread spectrum code of the accumulated signal to obtain a complex signal specifically includes:

Extract the symbol of the accumulated signal to obtain a binary sequence;

The binary sequence is multiplied by the accumulated signal to obtain a complex signal.

Optionally, the multi-frequency ionospheric scintillation model is:

Among them, ρ _s,k is the amplitude of the k-th sample signal, θ _s,k is the phase of the k-th sample signal, q is the order of the multi-frequency ionospheric scintillation model, and Γ _i is the gain coefficient of the multivariate autoregressive model set, κ is a constant, ρ _s,ki is the amplitude of the ki-th sample signal, θ _s,ki is the phase of the ki-th sample signal, e _ρ,k is a zero-mean Gaussian random variable, ∑ _ρ and ∑ _θ are Noise covariance matrix for a multiple autoregressive model.

For achieving the above object, the present invention also provides the following scheme:

A multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies, comprising a capture unit and a tracking unit;

The capture unit is used to receive the navigation signals of each Beidou satellite in real time;

The tracking unit is connected to the capture unit, and the tracking unit includes:

A transmission time determination module, connected to the capture unit, for the navigation signal of any Beidou satellite, according to the position of the Beidou satellite at the previous moment, the position of the receiver, the transmission time of the navigation signal at the previous moment and the current moment With the time interval of the previous moment, the linear interpolation method is used to determine the transmission time of the navigation signal from the Beidou satellite to the receiver at the current moment; the position of the Beidou satellite at the initial moment and the transmission time of the navigation signal are predetermined;

a Doppler frequency determination module, connected to the transmission time determination module, for determining the Doppler frequency of the navigation signal according to the transmission time;

a carrier erasing module, respectively connected with the Doppler frequency determination module and the capture unit, for erasing the carrier of the navigation signal according to the Doppler frequency to obtain a carrier erasure signal;

A navigation erasing module, connected with the carrier erasing module, is used for using network enhancement system information to erase the navigation information of the carrier erasing signal to obtain a navigation erasing signal;

an accumulation module, connected with the navigation erasure module, for dividing the navigation erasure signal into a plurality of signal blocks according to the spreading code period of the navigation signal, and coherently accumulating the plurality of signal blocks to obtain an accumulation Signal;

a spread spectrum code erasing module, connected with the accumulation module, for erasing the spread spectrum code of the accumulated signal to obtain a complex signal;

The optimization module is used to optimize the state space formula of the Kalman filter based on the multi-frequency ionospheric scintillation model to obtain the optimized Kalman filter; the multi-frequency ionospheric scintillation model adopts the multivariate autoregressive model, according to the Beidou B1C , B2a and B1I frequency sample signals transmitted by modeling the amplitude and phase of the ionospheric scintillation component;

The filtering module is respectively connected with the spreading code erasing module and the optimizing module, and is used for filtering the complex signal by using the optimized Kalman filter to obtain the tracking signal at the current moment.

Optionally, the Doppler frequency determination module includes:

a satellite speed determination submodule, connected to the transmission time determination module, for determining the running speed of the Beidou satellite at the current moment according to the transmission time;

The frequency determination sub-module is connected with the satellite speed determination sub-module, and is used for determining the Doppler frequency of the navigation signal according to the operating speed of the Beidou satellite at the current moment.

Optionally, the carrier erasing module includes:

a Doppler frequency shift determination submodule, connected to the Doppler frequency determination module, and configured to determine the Doppler frequency shift of the navigation signal according to the Doppler frequency;

a carrier determination submodule, connected to the Doppler frequency shift determination submodule, for determining the carrier of the navigation signal according to the Doppler frequency shift;

The erasing submodule is respectively connected with the carrier determination submodule and the acquisition unit, and is used for erasing the carrier of the navigation signal to obtain a carrier erasing signal.

According to the specific embodiment provided by the present invention, the present invention discloses the following technical effects: sequentially erasing the navigation signal carrier, navigation information and spread spectrum code to obtain a complex signal, and using a multivariate autoregressive model to determine the amplitude and phase of the ionospheric scintillation component Modeling, and then including them into the state equation of the open-loop Kalman filter, the complex signal is filtered by the optimized Kalman filter, avoiding the possibility of strong flicker causing the traditional closed-loop tracking loop to lose lock, At the same time, both the availability and accuracy of the receiver tracking loop under the influence of strong scintillation are taken into account.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative labor.

1 is a flowchart of a multi-frequency open-loop receiver tracking method under extreme ionospheric anomalies of the present invention;

2 is a block diagram of an open-loop receiver for processing strong flicker signals;

FIG. 3 is a schematic diagram of the module structure of the multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies according to the present invention.

Symbol Description:

Acquisition unit-1, tracking unit-2, transmission time determination module-21, Doppler frequency determination module-22, carrier erasure module-23, navigation erasure module-24, accumulation module-25, spreading code erasure Module-26, Optimization Module-27, Filtering Module-28.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

The purpose of the present invention is to provide a multi-frequency open-loop receiver tracking method and system under extreme ionospheric anomalies, using a multivariate autoregressive model to model the ionospheric scintillation component, and then including it in the open-loop loop filter In the state equation, the advantages of the multi-frequency architecture are used to take into account both the availability and accuracy of the receiver tracking loop under the influence of strong ionospheric scintillation.

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

The working principle of the receiver based on the PLL/DLL loop is as follows: after the signal is input, the acquisition module first identifies all visible satellites of the user. If a satellite is visible, a rough estimate of the signal frequency and code phase needs to be given, and then the tracking module The two are refined and the values are tracked as the signal characteristics change over time. When the signal is tracked correctly, the C/A code and carrier can be removed from the signal. After tracking, the navigation data can be demodulated and calculated. Pseudorange.

As shown in FIG. 1 and FIG. 2 , the multi-frequency open-loop receiver tracking method under extreme ionospheric anomalies of the present invention includes:

S1: Receive the navigation signals of each Beidou satellite in real time. Specifically, the total navigation signal r[n] received by the receiver is:

是一个通用的相位贡献，η[n]为热噪声，接收机的转换器在GNSS中频信号上以采样频率

运行。Among them, n represents the discrete signal, N _sat is the number of Beidou satellites, P[n] is the strength (power) of the received signal at the output end of the receiver analog-to-digital converter, d _i is the navigation information of the i-th Beidou satellite, T _s is the sampling period, τ _i is the code delay of the ith Beidou satellite, c _i is the spreading code of the ith Beidou satellite; f _i =f _IF +f _D is the carrier frequency of the navigation signal of the ith Beidou satellite, f _IF is the nominal intermediate frequency, f _D is the Doppler frequency shift;

is a general phase contribution, η[n] is the thermal noise, and the receiver's converter samples the GNSS IF signal at the sampling frequency

run.

S2: For the navigation signal of any Beidou satellite, the linear interpolation method is adopted according to the position of the Beidou satellite at the previous moment, the position of the receiver, the transmission time of the navigation signal at the previous moment, and the time interval between the current moment and the previous moment. Determine the transmission time of the navigation signal from the Beidou satellite to the receiver at the current moment. The position of the Beidou satellite at the initial moment and the transmission time of the navigation signal are predetermined.

S3: Determine the Doppler frequency of the navigation signal according to the transmission time.

S4: Erasing the carrier of the navigation signal according to the Doppler frequency to obtain a carrier erased signal. Specifically, the carrier erasure signal x[n] is:

S5: Using the network enhancement system information, erasing the navigation information of the carrier erasure signal to obtain a navigation erasure signal. Specifically, using A-GNSS (Assisted-Global Navigation Satellite System, Network Augmentation System) information, an accurate copy of the navigation information is generated, and the navigation information is erased.

The navigation erase signal z[n] is:

S6: Divide the navigation erasure signal into multiple signal blocks according to the spreading code period of the navigation signal, and perform coherent accumulation on the multiple signal blocks to obtain an accumulated signal. Specifically, the following formula is used to coherently accumulate multiple signal blocks to obtain an accumulated signal:

Among them, w[n] is the accumulated signal, L is the number of spreading code cycles, z[n+kN] is the kN-th signal block, N is the number of samples in each signal block, and n represents the discrete signal.

Due to the presence of thermal noise η[n], the pseudorandom noise code c _i is not visible, so the pseudorandom noise code cannot be estimated and removed. In principle, pseudorandom noise codes can be removed by erasure operations, but this requires sub-chip-level time synchronization and fine-grained assistance. This condition is difficult to meet with only appropriate A-GNSS information and knowledge of the receiver's position. Since thermal noise can be modeled as a zero-mean Gaussian random variable, the accumulation process can increase the signal-to-noise ratio of the signal until the modulated spreading code in the navigation signal emerges from the noise floor.

In this embodiment, the navigation signal z[n] is divided into a plurality of signal blocks of length T _code , where T _code is the period of the spreading code. Assuming that a cycle consists of N samples, L cycles are coherently added to obtain a signal w[n] of length N.

Some residual distortion remains due to other unmodeled effects that cannot be averaged to zero by the accumulation process, and due to some residual noise contribution. Therefore, given a fixed sampling frequency f _s , increasing the number L of spreading code periods, the noise contribution tends to be averaged out, but this requires many received signal segments, ie a large observation window. Due to the non-stationary nature of the flickering process, the statistical distribution of the signal amplitude varies with time, if L is too large it will not be able to capture significant changes in the statistical distribution as they will all be included in the same observation window, so L must be weighed in the analysis. Resolution and ability to reduce the effects of noise.

为：In addition, because the Doppler effect will not only change the carrier frequency, but also change the code rate, causing it to stretch and compress. Assuming that R _c is the nominal chip rate and f _L1 is the transmission frequency, the actual chip rate at time t can be found

for:

where f _D (t) is the Doppler shift on the carrier at time t.

Given a fixed sampling frequency f _s , the time-varying code rate causes the number of samples per chip to vary with the period. Furthermore, _fs and _Rc are unlikely to be multiples of each other, so the same chip may not be represented by the same number of samples in subsequent PRN code cycles, and the chips of subsequent samples may not be perfectly aligned, thus Threats to the effect of coherent accumulation of code cycles. If the converted samples are not removed from w[n], the residual modulation remains in y[n] after code erasure. For this reason, the present invention employs an algorithm that discards converted samples, both before and after symbol conversion, to remove converted samples from the output signal and prevent residual modulation from remaining in the signal after erasing spreading codes. .

将二进制序列

乘以累加信号w[n]，即实现从累加信号中擦除扩频码，得到复信号：

在开环环路中采取自适应带宽和延长相干积分时间，进一步减少环路的跟踪抖动。S7: Erasing the spreading code of the accumulated signal to obtain a complex signal. Specifically, the sign of the accumulated signal is extracted to obtain a binary sequence. The binary sequence is multiplied by the accumulated signal to obtain a complex signal. In this embodiment, the sign of the accumulated signal is extracted by the sign operator to obtain the binary sequence:

binary sequence

Multiplying the accumulated signal w[n], that is, erasing the spread spectrum code from the accumulated signal, and obtaining the complex signal:

Adopt adaptive bandwidth and extend the coherent integration time in the open loop to further reduce the tracking jitter of the loop.

S8: Based on the multi-frequency ionospheric scintillation model, the state space formula of the Kalman filter is optimized to obtain an optimized Kalman filter; A sample signal transmitted at the B1I frequency, modeled on the magnitude and phase of the ionospheric scintillation component.

S9: Use the optimized Kalman filter to filter the complex signal to obtain a tracking signal at the current moment. The tracking signal at the current moment is used to track the Beidou satellite. According to the tracking signal, the pseudorange can be calculated, and then the navigation and positioning can be realized.

GNSS open-loop processing utilizes statically known receiver positions and reference oscillators to generate an accurate local replica of the reference carrier. When the receiver's reference position and time are known, and a network connection is available that provides A-GNSS messages, certain components of the signal can be correctly predicted. They are removed from the input signal, leaving only random contributions caused by thermal noise and other disturbances, including flickering effects. The scintillation contribution can be isolated from the GNSS signal.

Before the onset of a strong flicker event, the receiver should be in steady-state tracking and a valid receiver time solution has been obtained. Specifically, in step S2, it is assumed that at time T, the received signal is transmitted from the satellite at time T-Δt ₁ , where Δt ₁ is the signal propagation time. X ^SV (T-Δt ₁ ) is the satellite position at the signal transmission time T-Δt ₁ , and X _RX is the position of the receiver. A signal arriving at the receiver at T+ΔT is transmitted from the satellite at T+ΔT-Δt ₂ , where Δt ₂ is the signal propagation time. Δt ₂ and Δt ₁ may not be equal because the satellite has moved from X ^SV (T-Δt ₁ ) to X ^SV (T+ΔT-Δt ₂ ). In order to predict the Doppler frequency at the reception time T+ΔT, the value of Δt ₂ needs to be determined. Since ΔT is very small, the variation of the pseudorange over this time period can be approximated as linearly dependent on ΔT, and then Δt ₂ can be obtained by simple linear interpolation.

Tx is the time at which the signal transmitted at T-Δt ₁ +ΔT is received, and _{tx is} the corresponding propagation time. So the process of calculating Δt ₂ consists of:

The ephemeris parameters are used to determine the satellite's position X ^SV (T-Δt ₁ +ΔT) at T-Δt ₁ +ΔT.

Δt _x =||X ^SV (T-Δt ₁ +ΔT)-X _RX ||/C;

T _x =T-Δt ₁ +ΔT+Δt _x ;

Δt ₂ =ΔT(Δt _x -Δt ₁ )/(T _x -T)+Δt ₁ ;

Among them, C is the speed of light, X _RX is the position of the receiver, Δt _x is the signal transmission time calculated according to Δt ₁ and X _RX .

At this time, according to Δt ₂ and the ephemeris parameters, the running speed V ^SV of the satellite at the time of transmitting the signal T+ΔT-Δt ₂ is calculated.

Further, step S3 specifically includes:

S31: Determine the running speed of the Beidou satellite at the current moment according to the transmission time.

S32: Determine the Doppler frequency of the navigation signal according to the operating speed of the Beidou satellite at the current moment. Specifically, the following formula is used to determine the Doppler frequency of the Beidou satellite navigation signal:

为导航信号的多普勒频率，I为接收机到北斗卫星的单位方向矢量，V^SV为当前时刻北斗卫星的运行速度，

为接收机时钟频率偏移估计，可通过对闪烁开始之前的安静时期的多普勒残差求平均确定。in,

is the Doppler frequency of the navigation signal, I is the unit direction vector from the receiver to the Beidou satellite, V ^SV is the running speed of the Beidou satellite at the current moment,

For receiver clock frequency offset estimation, it can be determined by averaging the Doppler residuals for the quiet period before the onset of flickering.

Further, the Doppler ^residual is the difference between the frequency estimated based on the closed-loop algorithm and the frequency calculated based on the receiver-satellite relative motion, and the receiver clock frequency is determined according to the following formula in this embodiment: offset estimation

为基于闭环算法(CLT算法)估计的频率，<>为取时间平均。in,

is the frequency estimated based on the closed-loop algorithm (CLT algorithm), and <> is the time average.

In the open loop loop, the known network enhancement system information is used to obtain the Doppler frequency of the navigation signal. Combined with the satellite position, satellite speed, and the position and reference time of the receiver, the transmission time of the navigation signal is obtained by linear interpolation, and then the transmission time of the navigation signal is obtained by linear interpolation. The Doppler frequency of the navigation signal is obtained to generate an accurate local reference carrier to ideally erase the RF carrier.

The present invention does not include DLL (delay locked loop, delay locked loop) or FLL (frequency locked loop, frequency locked loop), and demodulates the signal to baseband by removing the residual carrier at frequency f _i . Treat the receiver position as a known quantity and solve the distance equation for each satellite signal to obtain the clock bias. The Doppler frequency is predicted using the average deviation from all available satellite signals, then the carrier is erased to demodulate the signal to baseband.

Further, step S4 specifically includes:

S41: Determine the Doppler frequency shift of the navigation signal according to the Doppler frequency.

S42: Determine the carrier of the navigation signal according to the Doppler frequency shift.

S43: Erasing the carrier of the navigation signal to obtain a carrier erasing signal.

Since ionospheric scintillation is frequency dependent, and different satellite links are affected by different propagation conditions. For different frequency signal components of the same satellite, although phase perturbations may be correlated, deep amplitude decay tends to occur at different times for different frequency signals, allowing the use of multi-frequency architectures for inter-frequency assistance. Ionospheric scintillation can have a serious impact on carrier phase measurements and pseudorange observations. In order to be able to extract the required phase components for positioning from the scintillation components, the magnitude and phase of the ionospheric scintillation can be constructed using the multivariate autoregressive model formula. modulo, and then embed them into the state-space formulation of the Kalman filter.

In a multi-frequency architecture, the receiver can make multiple measurements on different frequencies of a single satellite. For example, using BDS (BeiDou Navigation Satellite System) sample signals transmitted on frequencies B1C, B2a and B1I, the measured values are:

为B1C频率上的第k个样本信号，

为B2a频率上的第k个样本信号，

为B1I频率上的第k个样本信号，

为B1C频率上的第k个样本信号的信号幅度，

为B2a频率上的第k个样本信号的信号幅度，

为B1I频率上的第k个样本信号的信号幅度，

为B1C频率上的第k个样本信号的相位，

为B2a频率上的第k个样本信号的相位，

为B1I频率上的第k个样本信号的相位，d代表本地生成的载波信号，s代表接收到的信号，j是虚数单位，

为B1C频率上的第k个样本信号的热噪声，

为B2a频率上的第k个样本信号的热噪声，

为B1I频率上的第k个样本信号的热噪声。in,

is the kth sample signal on the B1C frequency,

is the kth sample signal on the frequency B2a,

is the kth sample signal on the B1I frequency,

is the signal amplitude of the kth sample signal at the B1C frequency,

is the signal amplitude of the kth sample signal at frequency B2a,

is the signal amplitude of the kth sample signal at the B1I frequency,

is the phase of the kth sample signal at the B1C frequency,

is the phase of the kth sample signal at frequency B2a,

is the phase of the kth sample signal at the B1I frequency, d represents the locally generated carrier signal, s represents the received signal, j is the imaginary unit,

is the thermal noise of the kth sample signal at the B1C frequency,

is the thermal noise of the kth sample signal at frequency B2a,

is the thermal noise of the kth sample signal at the B1I frequency.

In this embodiment, the multi-frequency ionospheric scintillation model is:

Among them, ρ _s,k is the amplitude of the k-th sample signal, θ _s,k is the phase of the k-th sample signal, q is the order of the multi-frequency ionospheric scintillation model, which is determined by how the model approximates the actual amplitude and phase , 3≥q≥1, Γ _i is the set of gain coefficients of the multivariate autoregressive model, κ is a constant, ρ _s,ki is the amplitude of the ki-th sample signal, θ _s,ki is the phase of the ki-th sample signal, e _ρ,k are Gaussian random variables with zero mean, and ∑ _ρ and ∑ _θ are the noise covariance matrices of the multiple autoregressive model. The amplitude and phase of the first sample signal are the initial values.

矩阵中的每一个元素都具有维度M*M，由频带数量给出，B_M表示B1C、B2a和B1I这些北斗信号，共M个频带，

Each element in the matrix has dimension M*M, which is given by the number of frequency bands, B _M represents the Beidou signals of B1C, B2a and B1I, with a total of M frequency bands,

The purpose of the multi-frequency ionospheric scintillation model recursive algorithm is to derive the optimal value of the gain coefficient matrix according to the estimation error, minimize the mean square error, and gradually correct the initial estimated value.

The noise covariance matrices ∑ _ρ and ∑ _θ of multi-frequency ionospheric scintillation can well reflect the inter-frequency correlation of time series. From the estimated noise covariance, it is found that although ∑ _ρ is almost diagonal, that is, the ionospheric scintillation amplitude has no correlation, the significant values on the main diagonal appear in ∑ _θ , that is, the ionospheric scintillation phase has higher frequency-to-frequency correlation.

Since each frequency does not undergo deep fading at the same time, a multi-frequency ionospheric scintillation model and a multivariate autoregressive model are used to model the magnitude and phase of the ionospheric scintillation components, and the parameters of the multivariate autoregressive model are selected from the scintillation data to independently The flicker gain component of the analog signal.

Specifically, the state space formula of the optimized Kalman filter is:

及

为系数矩阵，k|k-1表示在时间k处使用到时间k-1的测量值的预测估计值，

及

从θ_s,k中得到，

及

从ρ_s,k中得到。in,

and

is the coefficient matrix, k|k-1 represents the predicted estimate at time k using the measurement up to time k-1,

and

Obtained from θ _s,k ,

and

from ρ _s,k .

In order to further reduce the tracking jitter in the open loop, the present invention adopts the method of adaptive bandwidth and prolonging the coherent integration time, and controls the amount of noise allowed to enter the loop filter through the noise bandwidth _Bn . The dynamic performance of the tracking loop, and the narrower bandwidth helps to ensure more accurate tracking; coherent integration refers to the time length of integration and accumulation. Long coherent integration time can make the tracking loop highly sensitive to weak signals, while coherent integration time Short can ensure robustness to highly dynamic signals, the longer the integration time or the smaller the correlation interval, the better the tracking accuracy, and the coherent integration time is limited by the period of the navigation data. Adjust the values of noise bandwidth and coherent integration time according to flicker. The invention adopts adaptive bandwidth and prolongs coherence time, which helps to improve the tracking precision of the open loop.

In addition, the present invention uses the skewness index R4 to determine the severity of the amplitude flicker.

Specifically, the S4 index expresses the severity of the amplitude flicker, which is defined as the normalized variance of the received signal strength:

Among them, I is the signal strength, the signal strength is calculated according to the receiver output, I=|R| ² , R is the amplitude envelope of the received signal; <> represents the time average value.

Due to slow oscillations due to antenna patterns, tropospheric scatter and multipath reflections from ground objects, filtering is required to eliminate signal amplitude trends. A 6th-order low-pass Butterworth filter with a cutoff frequency of 0.1 Hz is used to obtain a low-pass filtered < P> and <N>, P is the signal power of the tracking signal y[n], and N is the noise power of the tracking signal y[n].

Then use the P and <P> sequences to estimate the actual signal strength variance over 1 minute:

为：where M is the total number of samples in 1 minute. Average signal power over the same period

for:

Therefore, the S4 index is:

Also, R is the assumed normalized signal amplitude:

_The correlator output to compute S4 does not exist in the open-loop architecture, however the samples after Doppler removal and navigation information erasure are still available after accumulation, similar to the correlator output, albeit at a significantly different rate, these samples Still contains information about fluctuations due to flicker, which can be detected by defining new metrics based on the statistical characteristics of the histogram.

A statistical measure of the flicker amplitude using skewness R based _on the histogram of processed samples (normalized signal amplitude at each sample point) to characterize the severity of amplitude flicker in an open-loop loop, skewness is the symmetry A measure of the degree to which the probability distribution of a real-valued random variable lacks symmetry about its mean.

For univariate X ₁ , X ₂ , X ₃ the skewness R ₄ is estimated as:

为X₁到X_i的均值，σ为跟踪信号强度的标准差，M为样本数。由于闪烁活动会改变变量分布的形状，从而改变其对称性。当存在闪烁时，样本的直方图显着偏离高斯分布，因此，可以使用基于偏度的度量来估计闪烁活动。Among them, X _i represents the intensity of the tracking signal y[n] at a certain sampling point,

is the mean of X ₁ to X _i , σ is the standard deviation of the tracking signal strength, and M is the number of samples. Since the flickering activity changes the shape of the variable distribution, it changes its symmetry. When flicker is present, the histogram of the samples deviates significantly from a Gaussian distribution, therefore, a skewness-based measure can be used to estimate flicker activity.

The amplitude flicker index is used to measure the intensity of flicker on the signal. The better the effect of the previous multi-frequency open-loop flicker suppression measures, the smaller the calculated amplitude flicker index should be.

The invention proposes a multi-frequency open-loop loop tracking method. Open-loop processing uses static known receiver positions and reference oscillators to generate accurate copies of the reference carrier and navigation information, erase the carrier and navigation information, and use coherent accumulation to erase pseudo-random codes. Using the statistical relationship between scintillation in different frequency bands, the amplitude and phase components of ionospheric scintillation are modeled as a MAR (Multiple autoregressive ar) process, and an enhanced state space formula considering multiple frequencies is studied. In the state to be tracked by the loop filter, the problem of carrier tracking accuracy is solved.

As shown in FIG. 3 , the multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies of the present invention includes a capture unit 1 and a tracking unit 2 .

Wherein, the capture unit 1 is used to receive the navigation signals of each Beidou satellite in real time.

The tracking unit 2 is connected with the acquisition unit 1, and the tracking unit 2 includes: a transmission time determination module 21, a Doppler frequency determination module 22, a carrier erasure module 23, a navigation erasure module 24, an accumulation module 25, Spread spectrum code erasing module 26 , optimization module 27 and filtering module 28 .

Wherein, the transmission time determination module 21 is connected to the capture unit 1, and the transmission time determination module 21 is used for the navigation signal of any Beidou satellite, according to the position of the Beidou satellite and the position of the receiver at the previous moment. , The transmission time of the navigation signal at the previous moment and the time interval between the current moment and the previous moment, and the linear interpolation method is used to determine the transmission time of the navigation signal from the Beidou satellite to the receiver at the current moment. The position of the Beidou satellite at the initial moment and the transmission time of the navigation signal are predetermined.

The Doppler frequency determination module 22 is connected to the transmission time determination module 21, and the Doppler frequency determination module 22 is configured to determine the Doppler frequency of the navigation signal according to the transmission time.

Specifically, the Doppler frequency determination module 22 includes: a satellite velocity determination sub-module and a frequency determination sub-module.

Wherein, the satellite speed determination sub-module is connected with the transmission time determination module 21, and the satellite speed determination sub-module is used for determining the operation speed of the Beidou satellite at the current moment according to the transmission time.

The frequency determination sub-module is connected with the satellite speed determination sub-module, and the frequency determination sub-module is configured to determine the Doppler frequency of the navigation signal according to the operating speed of the Beidou satellite at the current moment.

The carrier erasing module 23 is respectively connected with the Doppler frequency determination module 22 and the acquisition unit 1, and the carrier erasing module 23 is used to remove the carrier wave of the navigation signal according to the Doppler frequency. Erasing to get the carrier erase signal.

Specifically, the carrier erasing module 23 includes: a Doppler frequency shift determining submodule, a carrier determining submodule, and an erasing submodule.

Wherein, the Doppler frequency shift determination sub-module is connected with the Doppler frequency determination module 22, and the Doppler frequency shift determination sub-module is used to determine the multi-frequency of the navigation signal according to the Doppler frequency Puller shift.

The carrier determination submodule is connected to the Doppler frequency shift determination submodule, and the carrier determination submodule is configured to determine the carrier of the navigation signal according to the Doppler frequency shift.

The erasing submodule is respectively connected with the carrier determining submodule and the capturing unit 1, and the erasing submodule is used for erasing the carrier of the navigation signal to obtain a carrier erasing signal.

The navigation erasing module 24 is connected with the carrier erasing module 23, and the navigation erasing module 24 is used to use the network enhanced system information to erase the navigation information of the carrier erasing signal to obtain the navigation erasing signal. .

The accumulation module 25 is connected to the navigation erasure module 24, and the accumulation module 25 is configured to divide the navigation erasure signal into a plurality of signal blocks according to the spreading code period of the navigation signal, and combine the plurality of signal blocks. The signal blocks are coherently accumulated to obtain an accumulated signal.

The spreading code erasing module 26 is connected to the accumulating module 25, and the spreading code erasing module 26 is used for erasing the spreading code of the accumulated signal to obtain a complex signal.

The optimization module 27 is used to optimize the state space formula of the Kalman filter based on the multi-frequency ionospheric scintillation model to obtain an optimized Kalman filter; the multi-frequency ionospheric scintillation model adopts a multiple autoregressive model, according to The sample signals transmitted on the B1C, B2a and B1I frequencies of Beidou are obtained by modeling the amplitude and phase of the ionospheric scintillation components.

The filtering module 28 is respectively connected with the spreading code erasing module 26 and the optimization module 27, and the filtering module 28 is used to filter the complex signal by using the optimized Kalman filter to obtain the current moment. tracking signal.

In addition, developers must consider not only software functionality but also execution performance when building a software receiver. The high computational throughput required in the signal acquisition and signal tracking process prevents a standard software receiver using a SISD (Single instruction Single data) algorithm on a CPU (central processing unit) from working in real time. Working in conjunction with the CPU is the GPU (graphics processing unit). A GPU consists of a large number of parallel processors with high floating-point performance and high memory bandwidth. It can be used to speed up the acquisition and tracking process in software receivers.

Compared with the prior art, the multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies of the present invention has the same beneficial effects as the above-mentioned multi-frequency open-loop receiver tracking method under extreme ionospheric anomalies, and will not be repeated here.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method.

In this paper, specific examples are used to illustrate the principles and implementations of the present invention. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the present invention; meanwhile, for those skilled in the art, according to the present invention There will be changes in the specific implementation and application scope. In conclusion, the contents of this specification should not be construed as limiting the present invention.

Claims (10)

1. a multi-frequency open-loop receiver tracking method under extreme ionosphere anomaly, is characterized in that, the multi-frequency open-loop receiver tracking method under described extreme ionosphere anomaly comprises: Real-time reception of navigation signals from various Beidou satellites; For the navigation signal of any Beidou satellite, according to the position of the Beidou satellite at the previous moment, the position of the receiver, the transmission time of the navigation signal at the previous moment, and the time interval between the current moment and the previous moment, the linear interpolation method is used to determine the current The transmission time of the navigation signal from the Beidou satellite to the receiver at the moment; the position of the Beidou satellite at the initial moment and the transmission time of the navigation signal are predetermined; determining the Doppler frequency of the navigation signal according to the transmission time; According to the Doppler frequency, the carrier of the navigation signal is erased to obtain a carrier erased signal; Using network enhancement system information, the navigation information of the carrier erasure signal is erased to obtain a navigation erasure signal; According to the spreading code period of the navigation signal, the navigation erasure signal is divided into multiple signal blocks, and the multiple signal blocks are coherently accumulated to obtain an accumulated signal; Erasing the spreading code of the accumulated signal to obtain a complex signal; Based on the multi-frequency ionospheric scintillation model, the state space formula of the Kalman filter is optimized to obtain the optimized Kalman filter; The amplitude and phase of the ionospheric scintillation component are modeled on the sample signal transmitted on the ionosphere; The complex signal is filtered by the optimized Kalman filter to obtain the tracking signal at the current moment. 2. The multi-frequency open-loop receiver tracking method under extreme ionospheric anomalies according to claim 1, wherein the determining the Doppler frequency of the navigation signal according to the transmission time specifically comprises: According to the transmission time, determine the running speed of the Beidou satellite at the current moment; The Doppler frequency of the navigation signal is determined according to the running speed of the Beidou satellite at the current moment. 3. The multi-frequency open-loop receiver tracking method under extreme ionosphere anomaly according to claim 2, is characterized in that, adopts following formula to determine the Doppler frequency of described Beidou satellite navigation signal:

in,

is the Doppler frequency of the navigation signal, I is the unit direction vector from the receiver to the Beidou satellite, V ^SV is the running speed of the Beidou satellite at the current moment,

is an estimate of the receiver clock frequency offset. 4. The multi-frequency open-loop receiver tracking method under extreme ionospheric anomaly according to claim 1, wherein, according to the Doppler frequency, the carrier of the navigation signal is erased to obtain a carrier Erase signals, including: determining a Doppler shift of the navigation signal according to the Doppler frequency; determining the carrier of the navigation signal according to the Doppler shift; The carrier wave of the navigation signal is erased to obtain a carrier wave erase signal. 5. The multi-frequency open-loop receiver tracking method under extreme ionospheric anomaly according to claim 1, is characterized in that, adopt following formula, carry out coherent accumulation with a plurality of signal blocks, obtain accumulation signal:

Among them, w[n] is the accumulated signal, L is the number of spreading code cycles, z[n+kN] is the kN-th signal block, N is the number of samples in each signal block, and n represents the discrete signal. 6. The multi-frequency open-loop receiver tracking method under extreme ionospheric anomaly according to claim 1, characterized in that, said erasing the spread spectrum code of the accumulated signal to obtain a complex signal, specifically comprising: Extract the symbol of the accumulated signal to obtain a binary sequence; The binary sequence is multiplied by the accumulated signal to obtain a complex signal. 7. The multi-frequency open-loop receiver tracking method under extreme ionospheric anomaly according to claim 1, wherein the multi-frequency ionospheric scintillation model is:

Among them, ρ _s,k is the amplitude of the k-th sample signal, θ _s,k is the phase of the k-th sample signal, q is the order of the multi-frequency ionospheric scintillation model, and Γ _i is the gain coefficient of the multivariate autoregressive model set, κ is a constant, ρ _s,ki is the amplitude of the ki-th sample signal, θ _s,ki is the phase of the ki-th sample signal, e _ρ,k is a zero-mean Gaussian random variable, ∑ _ρ and ∑ _θ are Noise covariance matrix for a multiple autoregressive model. 8. A multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies, characterized in that the multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies comprises a capture unit and a tracking unit; The capture unit is used to receive the navigation signals of each Beidou satellite in real time; The tracking unit is connected to the capture unit, and the tracking unit includes: A transmission time determination module, connected to the capture unit, for the navigation signal of any Beidou satellite, according to the position of the Beidou satellite at the previous moment, the position of the receiver, the transmission time of the navigation signal at the previous moment and the current moment With the time interval of the previous moment, the linear interpolation method is used to determine the transmission time of the navigation signal from the Beidou satellite to the receiver at the current moment; the position of the Beidou satellite at the initial moment and the transmission time of the navigation signal are predetermined; a Doppler frequency determination module, connected to the transmission time determination module, for determining the Doppler frequency of the navigation signal according to the transmission time; a carrier erasing module, respectively connected with the Doppler frequency determination module and the capture unit, for erasing the carrier of the navigation signal according to the Doppler frequency to obtain a carrier erasure signal; A navigation erasing module, connected with the carrier erasing module, is used for using network enhancement system information to erase the navigation information of the carrier erasing signal to obtain a navigation erasing signal; an accumulation module, connected with the navigation erasure module, for dividing the navigation erasure signal into a plurality of signal blocks according to the spreading code period of the navigation signal, and coherently accumulating the plurality of signal blocks to obtain an accumulation Signal; a spread spectrum code erasing module, connected with the accumulation module, for erasing the spread spectrum code of the accumulated signal to obtain a complex signal; The optimization module is used to optimize the state space formula of the Kalman filter based on the multi-frequency ionospheric scintillation model to obtain the optimized Kalman filter; the multi-frequency ionospheric scintillation model adopts the multivariate autoregressive model, according to the Beidou B1C , B2a and B1I frequency sample signals transmitted by modeling the amplitude and phase of the ionospheric scintillation component; The filtering module is respectively connected with the spreading code erasing module and the optimizing module, and is used for filtering the complex signal by using the optimized Kalman filter to obtain the tracking signal at the current moment. 9. The multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies according to claim 8, wherein the Doppler frequency determination module comprises: a satellite speed determination submodule, connected to the transmission time determination module, for determining the running speed of the Beidou satellite at the current moment according to the transmission time; The frequency determination sub-module is connected with the satellite speed determination sub-module, and is used for determining the Doppler frequency of the navigation signal according to the operating speed of the Beidou satellite at the current moment. 10. The multi-frequency open-loop receiver tracking system under extreme ionospheric anomalies according to claim 8, wherein the carrier erasure module comprises: a Doppler frequency shift determination submodule, connected to the Doppler frequency determination module, and configured to determine the Doppler frequency shift of the navigation signal according to the Doppler frequency; a carrier determination submodule, connected to the Doppler frequency shift determination submodule, for determining the carrier of the navigation signal according to the Doppler frequency shift; The erasing submodule is respectively connected with the carrier determination submodule and the acquisition unit, and is used for erasing the carrier of the navigation signal to obtain a carrier erasing signal.

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