Low earth orbit navigation augmentation signal digital domain self-interference cancellation method

Abstract

The application discloses a low-orbit navigation enhancement signal digital domain self-interference elimination method, which comprises the following steps: coupling a signal from a coupling port of a low-orbit navigation enhancement signal broadcast channel, obtaining a sampled self-interference reference signal after pre-processing; receiving a self-interference signal and a GNSS expected signal from a receiving antenna, obtaining a sampled receiving signal after processing; generating a local code and a local carrier, respectively performing parallel correlation with the obtained signals, and capturing a code phase; adjusting a time delay of the receiving signal and the self-interference reference signal, ensuring that the self-interference reference signal is ahead of the receiving signal, and obtaining a time delay adjusted receiving signal and a time delay adjusted self-interference reference signal; adopting an improved Kalman filtering method, adaptively adjusting filtering parameters, performing adaptive filtering interference elimination, and obtaining an interference eliminated signal; calculating a self-interference elimination capability, and judging whether a self-interference elimination process converges; if the self-interference elimination process converges, it is indicated that the digital domain self-interference elimination is completed.

Description

Technical Field

[0001] This invention belongs to the field of low-Earth orbit navigation enhancement, and specifically relates to a method for eliminating self-interference in the digital domain of low-Earth orbit navigation enhancement signals. Background Technology

[0002] With the completion of my country's BeiDou Navigation Satellite System and the modernization of GPS, the technical system and service performance of Global Navigation Satellite Systems (GNSS) based on medium and high Earth orbit (MEO) satellites have become basically mature. Meanwhile, with the rapid development of low Earth orbit (LEO) satellite constellations both domestically and internationally, especially the construction of mega-LEO internet constellations like Starlink, LEO navigation enhancement has become a hot development direction in the satellite navigation field. LEO constellations can complement MEO and MEO navigation constellations, enhancing the positioning accuracy, integrity, availability, and security of existing GNSS systems, and accelerating the convergence time for precise positioning.

[0003] Both domestic and international researchers have been conducting research on low-Earth orbit (LEO) navigation enhancement system technology and have proposed LEO constellation plans. XONA, an American company, has proposed a 300-satellite LEO navigation system to meet the navigation needs of challenging environments in the era of autonomous driving, and plans to broadcast dual-frequency LEO navigation signals in the L and C bands. Domestic research institutions and commercial companies have also verified LEO navigation enhancement technology by launching experimental satellites and broadcasting dual-frequency navigation enhancement signals in the L band.

[0004] For low-Earth orbit (LEO) navigation augmentation systems, broadcasting dual-frequency LEO navigation augmentation signals is a consensus, with broadcasting the L-band, especially the L-band of GNSS, being the preferred choice. However, while broadcasting LEO navigation augmentation signals, LEO satellites also need to receive medium- and high-Earth orbit (MEO) GNSS signals. This is necessary for orbit determination and for acquiring observational data to meet space-based monitoring requirements, including clock bias and orbit calculations. Therefore, when the broadcast LEO navigation augmentation signal and the received GNSS signal are on the same frequency band, the broadcast signal will become a strong self-interference signal relative to the received GNSS signal. To ensure the normal operation and accuracy of space-based monitoring, the problem of transmission and reception isolation must be solved. Summary of the Invention

[0005] The technical problem solved by this invention is: to address the problem of simultaneous transmission and reception isolation in the same frequency band when broadcasting LOR navigation enhancement signals in the GNSS L band, a digital domain self-interference cancellation method suitable for LOR navigation enhancement signals is proposed to reduce the impact of strong self-interference signals on weak desired signals and meet the needs of LOR navigation enhancement space-based monitoring and LOR navigation enhancement signal broadcasting.

[0006] The technical solution of this invention is: a method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals, comprising:

[0007] (1) A signal is coupled out from the coupling port of the broadcast channel of the low-orbit navigation enhancement signal, and after frequency conversion, filtering, amplification and ADC, a sampled self-interference reference signal is obtained; the self-interference signal and weak GNSS expected signal received by the receiving antenna after spatial isolation are obtained after LNA, filtering, frequency conversion, filtering, amplification and ADC, a sampled received signal is obtained.

[0008] (2) Generate a local code and a local carrier, and perform parallel correlation with the obtained received signal and self-interference reference signal to capture the code phase;

[0009] (3) Adjust the time delay of the received signal and the self-interference reference signal according to the captured code phase to ensure that the self-interference reference signal leads the received signal, so as to obtain the received signal and the self-interference reference signal after time delay adjustment.

[0010] (4) Using the received signal after time delay adjustment and the self-interference reference signal, the improved Kalman filtering method is adopted to adaptively adjust the filtering parameters and perform adaptive filtering interference cancellation to obtain the signal after interference cancellation.

[0011] (5) Calculate the self-interference cancellation capability based on the received signal after time delay adjustment and the signal after interference cancellation, and determine whether the self-interference cancellation process has converged; if it has converged, it means that the digital domain self-interference cancellation has been completed.

[0012] The received signal sampled in step (1), the nth sample value r IF (n) is represented as:

[0013]

[0014] In the formula, A k τ k θ k These represent the amplitude, delay, and phase of the received k-th self-interference signal, respectively, where τ0 is the path with the shortest delay. It is the path with the longest delay, and the range of the received self-interference signal delay distribution is... T s It is the sampling interval, f IF It is the intermediate frequency, r exp (n) represents a weak desired signal, N IF (n) represents noise, and c(t) is the low-orbit navigation enhancement baseband signal, denoted as... Where {c l} is the spreading code sequence, and p(t) is the chip waveform.

[0015] The self-interference reference signal sampled in step (1), the nth sampled value r IF (n) is represented as:

[0016] x ref (n)=A ref c(n·T s -τ ref cos(2πf) IF n·T s +θ ref )+N ref (n)

[0017] In the formula, A ref τ ref θ ref The amplitude, delay, and phase of the self-interference reference signal, N ref (n) represents the noise contained in the self-interference reference signal.

[0018] The capture code phase in step (2) includes:

[0019] Generate local in-phase carrier cos(2πf) IF n·T s ) and orthogonal carrier sin(2πf IF n·T s The intermediate frequency carrier of the digital down-conversion is obtained, expressed in complex form as: exp(-j2πf IF n·T s )=cos(2πf IF n·T s )-jsin(2πf IF n·T s );

[0020] Generate a local code c(n·T) for one code period s );

[0021] Parallel code acquisition is used to acquire the phase of the received signal code; the correlation value of the received signal is calculated.

[0022] corr rec (n)=IFFT{FFT{r IF (n)·exp(-j2πf IF n·T s )}conj(FFT{c(n·T s )})}

[0023] In the formula, FFT represents Fast Fourier Transform, IFFT represents Inverse Fast Fourier Transform, and conj represents the conjugate operation; find |corr rec (n) | The position corresponding to the maximum value n rec That is, the result of capturing the phase of the received signal code;

[0024] Based on the generated intermediate frequency carrier and local code, calculate the correlation value of the self-interference reference signal:

[0025] corr ref (n)=IFFT{FFT{x ref (n)·exp(-j2πf IF n·T s )}conj(FFT{c(n·T s )})}

[0026] Find |corr ref (n) | The position corresponding to the maximum value n ref That is, the code phase capture result of the self-interference reference signal.

[0027] Step (3) of adjusting the time delay between the received signal and the self-interference reference signal includes:

[0028] Compare n rec With n ref Size;

[0029] If n ref ≥n rec This indicates that the self-interference reference signal lags behind the received signal, requiring a delay in the received signal, with the number of delay samples being n. ref -n rec +n early In the formula, n early It is the time-delay adjusted self-interference reference signal, which, compared to the time-delay adjusted received signal, has a leading number of samples, and n early ≥1;

[0030] If n ref <n rec This indicates that the self-interference reference signal leads the received signal, and the self-interference reference signal needs to be delayed. The number of delay samples is n. rec -n ref -n early ;

[0031] Based on the comparison results above, a delay is applied to obtain the time-delay adjusted received signal r(n) and self-interference reference signal x(n).

[0032] Step (4) involves adaptive filtering to eliminate interference, resulting in a signal with interference eliminated, including:

[0033] Construct the observation equations and state equations;

[0034]

[0035] In the formula, x[n] is the self-interference reference signal vector, expressed as: x[n]=[x(n) x(n-1) … x(n-K+2) x(n-K+1)] T Where K is the filter order; w[n] represents the filter weight vector, denoted as w[n] = [w1(n) w2(n) … w K-1 (n) w K (n)] T And w[n] is the state to be estimated in the equation; N[n] is the measurement noise, with E(N[n])=0, cov(N[n])=δ n ,δ n >0;N w [n]=[n w,1 (n) n w,2 (n) … n w,K-1 (n) n w,K (n)] T The state noise of the filter weight vector w[n] is 0 for stable multipath signals and not 0 for scenarios with abrupt changes in multipath.

[0036] Parameter initialization; w(0) = 0 K×1 , Q(0)=0 K×K Where P0 is a positive number;

[0037] Based on the filter weight vector w[n], calculate the covariance matrix Q(n) of the system state noise:

[0038] Every N Q For each sample point, estimate Q(n) once, i.e.

[0039]

[0040] Wherein, the weight matrix W(n) is a K-row N-ary matrix. Q A column matrix, represented as:

[0041] W(n)=[w[nN Q ] w[nN Q +1] … w[n-2] w[n-1]] T ;

[0042] Adaptive Kalman filtering is performed on the filter weight vector w[n]:

[0043] One-step prediction of the state: w[n,n-1]=w[n-1];

[0044] One-step prediction of mean squared error: P[n,n-1]=P[n-1]+Q(n);

[0045] Filter gain update: H[n] = P[n,n-1]x[n](x T [n]P[n,n-1]x[n]+δ n ) -1 ;

[0046] State update: w[n-1] = w[n,n-1] + H[n](r[n] - x T [n]w[n,n-1]);

[0047] Mean squared error update: P[n]=(IH[n]x T [n])P[n,n-1]

[0048] Based on w[n] obtained after adaptive Kalman filtering, the signal s after interference cancellation is calculated. obj (n) = r[n] - x T [n]w[n].

[0049] The selection of K is related to the time delay distribution range, requiring...

[0050] Step (5) calculates the self-interference cancellation capability based on the received signal after time delay adjustment and the signal after interference cancellation, including:

[0051] The power value of the received signal is calculated. Where M is the number of sample points, power rec This means that the power value is calculated once for every M sample points;

[0052] The power of the signal after self-interference cancellation is calculated.

[0053] The self-interference cancellation capability is calculated based on the power value of the received signal and the power of the signal after self-interference cancellation. Converted to dB, it is expressed as:

[0054] Step (5) determines whether the self-interference cancellation process has converged, including: if G IC [dB]≥TH design If TH is true, it indicates that the self-interference elimination process has converged; otherwise, it has not converged. design This is the self-interference elimination threshold required by the design; if convergence is achieved, it indicates that self-interference elimination in the digital domain is complete.

[0055] The advantages of this invention compared to the prior art are:

[0056] (1) Existing digital domain interference cancellation methods in the field of low-orbit navigation enhancement mainly focus on adaptive filtering algorithms. This invention presents a complete digital domain self-interference cancellation structure and method, consisting of a code phase acquisition module, a time delay adjustment module, adaptive filtering interference cancellation, and a self-interference cancellation capability monitoring module.

[0057] (2) Existing digital domain interference cancellation methods for low-orbit navigation enhancement mainly employ adaptive filtering algorithms, such as LMS algorithm and improved LMS algorithm. This invention designs a digital domain self-interference cancellation algorithm based on improved Kalman filter. This method achieves an adaptive parameter adjustment function similar to Kalman filter by constructing observation equations and state equations similar to those of classical Kalman filter.

[0058] (3) The digital domain self-interference cancellation method for low-orbit navigation enhancement signals disclosed in this invention, through a code phase acquisition module and a time delay adjustment module, can adaptively adjust the relative time delay between the received signal and the self-interference reference signal, ensuring that the self-interference reference signal leads the received signal (this is generally assumed to be a prerequisite in existing technologies); by incorporating the estimation of the weight vector covariance matrix during the adaptive filtering process, it achieves adaptability to multipath dynamic scenarios; through self-interference cancellation capability monitoring, it can monitor whether convergence has occurred and re-initialize when the algorithm malfunctions, increasing reliability. It has the advantages of being adaptive, having fast convergence, strong dynamic adaptability, and high reliability. Attached Figure Description

[0059] Figure 1 This is a block diagram of the low-orbit navigation enhancement signal digital domain self-interference cancellation method disclosed in this invention;

[0060] Figure 2 This is a schematic diagram of code phase acquisition;

[0061] Figure 3 Block diagram for adaptive filtering interference cancellation;

[0062] Figure 4 Example of time-domain convergence results for self-interference elimination;

[0063] Figure 5 This is an example of the frequency domain result after self-interference cancellation convergence. Detailed Implementation

[0064] This invention addresses the issue of simultaneous transmission and reception isolation in the same frequency band when broadcasting LEO navigation enhancement signals in the GNSS L band. It proposes a digital domain self-interference cancellation method suitable for LEO navigation enhancement signals, which reduces the impact of strong self-interference signals on weak desired signals and meets the needs of LEO navigation enhancement space-based monitoring and LEO navigation enhancement signal broadcasting.

[0065] This invention discloses a method for generating and receiving high-power communication-conduction fusion navigation signals, as follows: Figure 1 As shown, it includes:

[0066] (1) Signal sampling. A signal is coupled out from the coupling port of the broadcast channel of the low-orbit navigation enhancement signal, and after frequency conversion, filtering, amplification, and ADC, the sampled self-interference reference signal is obtained; the spatially isolated self-interference signal and weak GNSS expected signal received from the receiving antenna are processed by LNA, filtering, frequency conversion, filtering, amplification, and ADC to obtain the sampled received signal.

[0067] 1) The received signal sampled, the nth sample value r IF (n) can be represented as:

[0068]

[0069] In the formula, the influence of the telegram is ignored, A k τ k θ k These represent the amplitude, delay, and phase of the received k-th self-interference signal, respectively, where τ0 is the path with the shortest delay. It is the path with the longest delay, and the range of the received self-interference signal delay distribution is... Ts is the sampling interval, f IF It is the intermediate frequency, r exp (n) represents a weak desired signal, N IF (n) represents noise, and c(t) is the low-orbit navigation enhancement baseband signal, expressed as:

[0070]

[0071] Among them, {c l} is the spreading code sequence, and p(t) is the chip waveform.

[0072] 2) The sampled self-interference reference signal, the nth sampled value r IF (n) can be represented as: x ref (n)=A ref c(n·T s -τ ref cos(2πf) IF n·T s +θ ref )+N ref (n)

[0073] In the formula, A ref τ ref θ ref The amplitude, delay, and phase of the self-interference reference signal, N ref (n) represents the noise contained in the self-interference reference signal.

[0074] (2) Code phase acquisition. Since it is a self-interference signal, Doppler is negligible, and only code phase acquisition is needed to determine the relative time delay between the received signal and the self-interference reference signal. The process is as follows: Figure 2 As shown, including

[0075] 1) Local carrier generation. Generate a local in-phase carrier cos(2πf). IF n·T s ) and orthogonal carrier sin(2πf IF n·T s The intermediate frequency carrier of the digital down-conversion is obtained, expressed in complex form as: exp(-j2πf IF n·T s )=cos(2πf IF n·T s )-j sin(2πf IF n·T s );

[0076] 2) Local code generation. Generate a local code c(n·T) for one code period. s ).

[0077] 3) Received signal code phase acquisition. Parallel code acquisition is used for received signal code phase acquisition. The correlation value of the received signal is calculated:

[0078] corr rec (n)=IFFT{FFT{r IF (n)·exp(-j2πf IF n·T s )}conj(FFT{c(n·T s )})}

[0079] In the formula, FFT represents Fast Fourier Transform, IFFT represents Inverse Fast Fourier Transform, and conj represents the conjugate operation. Find |corr rec (n) | The position corresponding to the maximum value n rec That is, the result of capturing the phase of the received signal code.

[0080] 4) Reference signal code phase acquisition. Based on the generated intermediate frequency carrier and local code, calculate the correlation value of the self-interference reference signal:

[0081] corr ref (n)=IFFT{FFT{x ref (n)·exp(-j2πf IF n·T s )}conj(FFT{c(n·T s )})}

[0082] Find |corr ref (n) | The position corresponding to the maximum value n ref That is, the code phase capture result of the self-interference reference signal.

[0083] (3) Delay Adjustment. Delay adjustment is based on the code phase acquisition results, adjusting the relative delay between the received signal and the self-interference reference signal to ensure that the self-interference reference signal leads the received signal, and only by n. early n sample points early ≥1, the process is as follows:

[0084] 1) Compare n rec With n re The size of f.

[0085] 2) If n ref ≥n rec This indicates that the self-interference reference signal lags behind the received signal, and the received signal needs to be delayed by n delay samples. ref -n rec +n early In the formula, n early It is the time-delay adjusted self-interference reference signal, and compared to the time-delay adjusted received signal, the number of leading samples, n early ≥1.

[0086] 3) If n ref <n rec This indicates that the self-interference reference signal leads the received signal, and the self-interference reference signal needs to be delayed by n samples. rec -n ref -n early .

[0087] 4) Based on the number of delayed samples, delay is applied to obtain the delayed received signal r(n) and the delayed self-interference reference signal x(n).

[0088] (4) Adaptive Filtering Interference Cancellation. Using the time-delay adjusted received signal and the time-delay adjusted self-interference reference signal, an improved Kalman filtering method is employed to adaptively adjust the filtering parameters and perform adaptive filtering interference cancellation, resulting in a signal with interference cancellation, such as... Figure 3 As shown. The specific steps are as follows:

[0089] 1) Construct the observation equation and the state equation.

[0090]

[0091] In the formula, x[n] is the self-interference reference signal vector, expressed as: x[n]=[x(n) x(n-1) … x(n-K+2) x(n-K+1)]T Where K is the filter order, and the selection of K is related to the range of multipath delay distribution, requiring... w[n] is the filter weight vector, denoted as w[n] = [w1(n) w2(n) … w K-1 (n) w K (n)] T And w[n] is the state to be estimated in the equation. N[n] is the measurement noise, and we have E(N[n])=0, cov(N[n])=δ n ,δ n >0. N w [n]=[n w,1 (n) n w,2 (n)... n w,K-1 (n) n w,K (n)] T The state noise of the filter weight vector w[n] is 0 for stable multipath signals and not 0 for scenarios with abrupt changes in multipath.

[0092] 2) Parameter initialization. w(0) = 0 K×1 , Q(0)=0 K×K Where P0 is a positive number, such as 100.

[0093] 3) Calculate the covariance matrix Q(n) of the system state noise based on the filter weight vector w[n]:

[0094] Every N Q For each sample point, estimate Q(n) once, i.e.

[0095]

[0096] Wherein, the weight matrix W(n) is a K-row N-ary matrix. Q A column matrix, represented as:

[0097] W(n)=[w[nN Q ] w[nN Q +1] … w[n-2] w[n-1]] T

[0098] Where, N Q The value is related to the dynamics of the multipath scenario and can be selected as 1000.

[0099] 4) Perform adaptive Kalman filtering on the filter weight vector w[n].

[0100] One-step prediction of the state: w[n,n-1]=w[n-1];

[0101] One-step prediction of mean squared error: P[n,n-1]=P[n-1]+Q(n);

[0102] Filter gain update: H[n] = P[n,n-1]x[n](x T [n]P[n,n-1]x[n]+δ n ) -1 ;

[0103] State update: w[n-1] = w[n,n-1] + H[n](r[n] - x T [n]w[n,n-1]);

[0104] Mean squared error update: P[n]=(IH[n]x T [n])P[n,n-1]

[0105] 5) Based on w[n] obtained after adaptive Kalman filtering, the interference-cancelled signal s is obtained. obj (n) = r[n] - x T [n]w[n].

[0106] (5) Convergence determination. Based on the received signal after time delay adjustment and the signal after interference cancellation, calculate the ratio of power before and after self-interference cancellation to determine whether convergence has occurred. If convergence has occurred, it indicates that self-interference cancellation in the digital domain has been completed. The ratio of power before and after self-interference cancellation serves as a basis for determining whether the self-interference cancellation process has converged and stabilized. On the other hand, if convergence is not achieved for a long time, it indicates that the algorithm has failed and the Kalman filter parameters need to be reinitialized.

[0107] The specific steps for calculating the ratio of power before and after self-interference cancellation and determining whether convergence has been achieved are as follows:

[0108] 1) Calculate the power value of the received signal. Where M is the number of sample points for the estimated power, power rec This indicates that the power value is calculated once for every M sample points, and r(m) represents the m-th sample value of the received signal.

[0109] 2) Calculate the power of the signal after self-interference cancellation. S obj This represents the m-th sampled value of the signal after interference cancellation.

[0110] 3) Calculation of self-interference cancellation capability.

[0111] The self-interference cancellation capability is: Converted to dB, it is expressed as:

[0112] 4) Convergence test. If G IC [dB]≥THdesign If the result is TH, it indicates that the self-interference cancellation process has converged and the self-interference cancellation in the digital domain is complete; otherwise, it has not converged. design The self-interference elimination threshold value is set according to the design requirements.

[0113] Figure 4 The time-domain convergence results of self-interference cancellation are presented. Figure 5 The converged frequency domain results are presented. Considering a scenario with 30 self-interference signals, and the multipath channel parameters abruptly changing at 3ms, the signals are analyzed using BPSK(10), with an intermediate frequency of 30.69MHz and an analysis bandwidth of ±15.345MHz. Q =1000. As can be seen, after a sudden change in the multipath channel, it can quickly and adaptively reconverge.

[0114] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals, characterized in that, include: A signal is coupled out from the coupling port of the broadcast channel of the low-orbit navigation enhancement signal, and after frequency conversion, filtering, amplification and ADC, a sampled self-interference reference signal is obtained; The spatially isolated self-interference signal and the desired GNSS signal received from the receiving antenna are processed by LNA, filtering, frequency conversion, filtering, amplification, and ADC to obtain the sampled received signal. Generate a local code and a local carrier, and perform parallel correlation with the obtained received signal and self-interference reference signal to capture the code phase; Based on the captured code phase, the time delay between the received signal and the self-interference reference signal is adjusted to ensure that the self-interference reference signal leads the received signal, thus obtaining the time-delay adjusted received signal and self-interference reference signal. By using the received signal after time delay adjustment and the self-interference reference signal, an improved Kalman filtering method is adopted to adaptively adjust the filtering parameters and perform adaptive filtering interference cancellation to obtain the interference-cancelled signal. Based on the received signal after time delay adjustment and the signal after interference cancellation, the self-interference cancellation capability is calculated, and it is determined whether the self-interference cancellation process has converged. If it has converged, it means that the digital domain self-interference cancellation has been completed. If it has not converged, the Kalman filter parameters are re-initialized and self-interference cancellation is performed again. The capture code phase includes: Generate local in-phase carrier with orthogonal carriers The intermediate frequency carrier obtained from digital downconversion is represented in complex form: ; Generate local code for one code period ; Parallel code acquisition is used to acquire the phase of the received signal code; the correlation value of the received signal is calculated. In the formula, FFT represents Fast Fourier Transform, IFFT represents Inverse Fast Fourier Transform, and conj represents the conjugate operation; find Position corresponding to the maximum value That is, the result of capturing the phase of the received signal code; Based on the generated intermediate frequency carrier and local code, calculate the correlation value of the self-interference reference signal: turn up Position corresponding to the maximum value That is, the code phase capture result of the self-interference reference signal; The adjustment of the time delay between the received signal and the self-interference reference signal includes: Compare and Size; if This indicates that the self-interference reference signal lags behind the received signal, requiring a delay in the received signal. The number of delay samples is... In the formula, It is the time-delay adjusted self-interference reference signal, which, compared to the time-delay adjusted received signal, has a higher number of leading samples, and ; if This indicates that the self-interference reference signal leads the received signal, and the self-interference reference signal needs to be delayed. The number of delay samples is... ; Based on the comparison results above, a delay is applied to obtain the received signal after time delay adjustment. and self-interference reference signal .

2. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 1, characterized in that, The sampled received signal, the nth sample value Represented as: In the formula, These represent the amplitude, delay, and phase of the received k-th self-interference signal, respectively. It is the path with the shortest latency. It is the path with the longest delay, and the range of the received self-interference signal delay distribution is... ; It is the sampling interval. It is the intermediate frequency. Indicates a weak expectation signal. Indicates noise. It is a low-orbit navigation enhancement baseband signal, represented as ,in It is a spreading code sequence. It is a chip waveform.

3. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 1, characterized in that, The sampled self-interference reference signal, the nth sampled value Represented as: In the formula, It refers to the amplitude, delay, and phase of the self-interference reference signal. This indicates the noise contained in the self-interference reference signal.

4. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 1, characterized in that, The adaptive filtering interference cancellation process, to obtain the interference-cancelled signal, includes: Construct the observation equations and state equations; In the formula, It is the self-interference reference signal vector, represented as: Where K is the filter order; Let the filter weight vector be denoted as . ,and The state to be estimated in the equation; N[n] is the measurement noise, and we have ; The filter weight vector The state noise, for a stable multipath signal, is... For scenarios involving multipath mutations, not for ; Kalman filter parameter initialization: , ,in, It is a positive number; Based on the filter weight vector Calculate the covariance matrix of the system state noise. : Every time N Q One sample point, estimated once ,Right now Among them, the weight matrix For row K N Q A column matrix, represented as: ； For the filter weight vector Perform adaptive Kalman filtering: One-step prediction of the state: ; One-step prediction of mean squared error: ; Filter gain update: ; Status Update: ; Mean squared error update: Based on the adaptive Kalman filter obtained The signal after interference cancellation is calculated. .

5. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 4, characterized in that, The selection of K is related to the time delay distribution range, requiring... .

6. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 1, characterized in that, The calculation of self-interference cancellation capability based on the received signal after time delay adjustment and the signal after interference cancellation includes: The power value of the received signal is calculated. Where M is the number of sample points, This indicates that the power value is calculated once for every M sample points; r(m) represents the m-th sample value of the received signal; The power of the signal after self-interference cancellation is calculated. Sobj(m) represents the m-th sampled value of the signal after interference cancellation; The self-interference cancellation capability is calculated based on the power value of the received signal and the power of the signal after self-interference cancellation. Converted to dB, it is expressed as: .

7. The method for eliminating self-interference in the digital domain of low-orbit navigation enhancement signals according to claim 6, characterized in that, The determination of whether the self-interference elimination process has converged includes: if If the result is 0, it indicates that the self-interference elimination process has converged; otherwise, it has not converged. Wherein, This is the self-interference elimination threshold required by the design; if convergence is achieved, it indicates that self-interference elimination in the digital domain is complete.

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