Synchronization and non-synchronization GNSS signal coherent integration gain mechanism analysis method

Abstract

This application relates to a method for analyzing the coherent integration gain mechanism of synchronous and asynchronous GNSS signals. The method includes: for synchronous signal generation scenarios, generating a local copy that maximizes the total correlation energy; calculating the coherent integration output based on the local copy and the intermediate frequency signal; introducing a pseudo-random code to normalize the correlation function and simplifying with residual frequency difference; obtaining the output signal; and then calculating the output signal-to-noise ratio (SNR) by combining it with a preset noise power, thus deriving the conclusion that the output SNR in synchronous scenarios is linearly proportional to the coherent integration time. For asynchronous signal relay scenarios, generating independent local copies for the real signal and multiple relayed signals respectively; calculating the conjugate correlation integral of the local copy and the mixed input signal and simplifying the integration result, deriving the expression for the output SNR in asynchronous scenarios, and concluding that it is proportional to the input SNR and the coherent integration time. This method can provide theoretical support for the optimized design of the acquisition and tracking link in GNSS array receivers.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals. Background Technology

[0002] Global Navigation Satellite Systems (GNSS), as a core infrastructure providing spatiotemporal reference, have been deeply integrated into key areas such as power synchronization, intelligent transportation, and drone navigation. The reliability of its services directly determines the security and stability of downstream applications. However, due to the inherent characteristics of "high orbit, low power, and open interface" during satellite-to-ground transmission, GNSS signals are highly susceptible to being misled by forged signals. By transmitting forged signals with structures highly similar to real GNSS signals, the positioning, navigation, and timing (PNT) results of receivers can be secretly altered. In recent years, this has led to numerous safety incidents, including drone crashes and vehicle trajectory deviations, becoming a core risk threatening the availability of GNSS systems. Based on the degree of synchronization between forged signals and real signals in the dimensions of code delay and Doppler shift, they can be divided into two categories: synchronously generated signals and asynchronously relayed signals. Synchronous GNSS signal generation is a high-precision signal replication and transmission technology. Its core lies in generating and broadcasting a set of radio frequency signals that are highly synchronized with the real satellite navigation signals in time. Asynchronous GNSS signal relay is a relay technology based on signal amplification. Its core lies in receiving and directly broadcasting a set of radio frequency signals that have an inherent time deviation from the real satellite navigation signals. The two have fundamentally different impacts on the receiver processing link due to differences in signal characteristics: the former's signal parameters are highly aligned with the real signal, resulting in superimposed correlation peaks in the receiver's correlation domain, which can directly drive the tracking loop to achieve seamless takeover and has stronger concealment; the latter's signal parameters deviate significantly from the real signal, manifesting as independent multiple correlation peaks in the correlation domain, but requiring the receiver to perform multi-channel parallel processing to achieve signal separation and suppression.

[0003] In the acquisition and tracking phase of a GNSS array receiver, coherent integration is a crucial preprocessing step for improving the signal-to-interference-plus-noise ratio (SINR), ensuring subsequent direction-of-arrival (DOA) estimation, and enhancing the accuracy of spoofing suppression. By integrating the signal in the time domain, the energy of the useful signal can be amplified while suppressing noise. However, existing research on coherent integration has significant limitations: most studies focus only on a single type of spoofing misleading signal, such as analyzing only asynchronous relay signals, without considering the differences in signal characteristics between synchronous and asynchronous GNSS signals to establish targeted coherent integration models. This results in an inability to explain core issues such as why code phase / Doppler deviations attenuate the integration gain during synchronous signal generation and why signal separation can be achieved through multiple tracking loops during asynchronous signal relay. Existing literature mainly qualitatively describes how coherent integration can improve SNR, but it does not derive the quantitative relationship between integration gain and key parameters in different scenarios, such as integration time, code phase deviation, and Doppler deviation, thus failing to provide a theoretical basis for receiver integration time configuration and tracking loop parameter optimization.

[0004] The aforementioned issues prevent GNSS array receivers from improving signal processing gain through optimized coherent integration strategies when facing complex electromagnetic environments, thus limiting the performance ceiling of subsequent detection and suppression algorithms. Therefore, it is urgent to deeply analyze the gain mechanism of coherent integration, considering the differentiated characteristics of synchronous and asynchronous GNSS signals, and establish a quantitative mathematical model to provide theoretical support for the optimized design of the acquisition and tracking link in GNSS array receivers. Summary of the Invention

[0005] Therefore, it is necessary to provide a method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals, which can provide theoretical support for the optimized design of the acquisition and tracking link of GNSS array receivers, in order to address the above-mentioned technical problems.

[0006] A method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals, the method comprising:

[0007] For synchronous signal generation scenarios, the intermediate frequency signal received in the GNSS array receiver is obtained. Based on the intermediate frequency signal, and taking into account the premise that the code delay between the generated signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, a local copy that maximizes the total correlation energy is generated.

[0008] The coherent integral output is calculated based on the local copy and the intermediate frequency signal. The pseudo-random code is introduced to normalize the correlation function and the residual frequency difference to simplify the coherent integral output, thereby generating the output signal after coherent integration in the synchronous signal generation scenario.

[0009] The signal power is calculated based on the output signal after coherent integration. The output signal-to-noise ratio is then calculated using the signal power and the pre-calculated noise power. Based on the output signal-to-noise ratio, it is deduced that the output signal-to-noise ratio in the synchronous signal generation scenario is linearly proportional to the coherent integration time.

[0010] For asynchronous signal forwarding scenarios, based on the intermediate frequency signal expression, and taking into account the premise that the phase difference between any two signal codes is greater than one chip and the receiver obtains the phase and Doppler estimation values ​​of each signal code through multi-peak acquisition, independent and precisely aligned local copies are generated for the real signal and multiple forwarded signals respectively, and multiple local copy expressions are output.

[0011] The correlation integral between the local copy and the conjugate of the mixed input signal is calculated. The correlation value is simplified by taking advantage of the characteristic that the correlation value is close to zero when the code phase delay is greater than one chip. Based on the simplified integration result, the expression for the output signal-to-noise ratio in the asynchronous signal forwarding scenario is derived, and it is concluded that the output signal-to-noise ratio is proportional to the input signal-to-noise ratio and the coherent integration time.

[0012] The aforementioned method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals first acquires the intermediate frequency (IF) signal from the GNSS array receiver and generates a local copy that maximizes the total correlation energy. Then, by calculating the coherent integral output, introducing a pseudo-random code to normalize the correlation function, and simplifying the residual frequency difference, it clarifies the attenuation effects of code phase delay and Doppler frequency difference on signal amplitude. It also points out that the common phase term caused by the residual frequency difference is eliminated when solving the covariance matrix. This not only explains the mechanism of integral gain attenuation in synchronous signal generation but also clarifies that the coherent integral result has no negative impact on subsequent DOA estimation. It provides a theoretical basis for balancing the effects of integration time and parameter deviation in synchronous scenarios, avoiding gain loss caused by blindly setting the integration time. In synchronous scenarios, the signal power is calculated based on the integrated output signal, and the output signal-to-noise ratio (SNR) is obtained by combining it with a preset noise power, deriving a quantization relationship where the output SNR is linearly proportional to the coherent integration time. In asynchronous scenarios, similarly, through simplification of the integration result and SNR derivation, it is concluded that the output SNR is proportional to the input SNR and the coherent integration time. These two sets of quantitative relationships directly provide clear standards for the configuration of receiver integration time. Based on the lower limit of the required output signal-to-noise ratio (SNR) of the system, the minimum coherent integration time required can be deduced, or based on the upper limit of the allowable integration delay, the achievable SNR improvement can be determined, completely solving the problem of lacking a basis for parameter optimization in the background. Simultaneously, in asynchronous scenarios, based on the premise that the intermediate frequency signal expression and the code phase difference are greater than one chip, and multi-peak acquisition is used to obtain parameter estimates, an independent and precisely aligned local copy is generated for each signal. By calculating the correlation integral between the local copy and the mixed signal, effective separation of the real signal and the spoofed signal is achieved. Furthermore, the derived SNR expression is determined solely by the target signal input SNR and the integration time, providing theoretical support for the configuration of the number of tracking loops and the parameter alignment accuracy requirements in asynchronous scenarios, ensuring the rationality of the multi-channel parallel processing design. This application transforms ambiguous technical issues in the background art into quantifiable and applicable theoretical conclusions through differential analysis of synchronous and asynchronous GNSS signals in coherent integration. It directly provides precise guidance for the optimization of integration strategies, loop design, and parameter configuration of the acquisition and tracking link of GNSS array receivers, effectively improving the accuracy of spoofing signal suppression. Attached Figure Description

[0013] Figure 1 This is a flowchart illustrating a method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals in one embodiment. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0015] In one embodiment, such as Figure 1 As shown, a method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals is provided, including the following steps:

[0016] Step 102: For the synchronous signal generation scenario, obtain the intermediate frequency signal received in the GNSS array receiver. Based on the intermediate frequency signal and the premise that the code delay between the generated signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, generate a local copy that maximizes the total correlation energy.

[0017] Based on the properties of the autocorrelation function of pseudo-random codes, when the code delay between the generated signal and the real signal is less than one chip, the generated signal and the real satellite signal can be considered coherent. Consider the first... The intermediate frequency signal received by each antenna element It is composed of a linear superposition of three identical PRN signals (one real signal and two generated signals) and noise, that is:

[0018] ;

[0019] No. Each signal component It can be represented as:

[0020] ;

[0021] in Represents the true signal. Represents the generated signal. It is the PRN code shared by all signals. They are the first The amplitude, data bits, code phase, intermediate frequency, Doppler shift, and initial carrier phase of each signal. It is the first The direction of arrival of the signal The decision is made by the antenna. Spatial phase. The mean is 0, and the power is Additive white Gaussian noise.

[0022] Due to the code phase of the generated signal and the real signal Since they are all within a single chip range, when the receiver acquires and stably tracks this mixed signal, it means that the receiver can generate a local copy. Its parameters To maximize the total relevance energy, the local replica is:

[0023] ;

[0024] Based on the core characteristic of synchronously generated signals, with a code delay of less than one chip, a local copy is designed to ensure that the correlation between the copy and the real signal plus the synchronously generated signal is maximized, providing a suitable reference benchmark for subsequent coherent integration to accurately extract signal energy.

[0025] Step 104: Calculate the coherent integral output based on the local copy and the intermediate frequency signal, introduce the pseudo-random code normalization correlation function and the residual frequency difference to simplify the coherent integral output, and generate the coherent integral output signal in the synchronous signal generation scenario.

[0026] When the coherent integration time is At that time, the coherent integral output is:

[0027] ;

[0028] make , ,Right now:

[0029] ;

[0030] For each item Then we have:

[0031] ;

[0032] Due to the coherent integration time If it is less than 20ms, then the data bits Constant as ,Right now:

[0033] ;

[0034] By introducing a normalized correlation function for pseudo-random codes And coherent integration time It is the code cycle If it is an integer multiple of , then it can be approximated as:

[0035] ;

[0036] because All are related to the tracking point It's very close, so For all Both are significantly nonzero real numbers. Let For the residual frequency difference, we have:

[0037] ;

[0038] Calculate the integral term:

[0039] ;

[0040] in The output signal after coherent integration is:

[0041] ;

[0042] It can be observed that the code phase delay and Doppler frequency difference between signals attenuate the signal amplitude after coherent integration. Furthermore, the Doppler frequency difference introduces a new phase term; however, it is important to emphasize that this common phase term is eliminated when solving the covariance matrix, and therefore does not affect the DOA estimation.

[0043] In synchronous signal generation scenarios, the generated signal must be highly consistent with the real signal at the Doppler frequency, or have a very small error, in order to achieve seamless takeover of the tracking loop. Therefore, residual frequency difference... ,therefore Phase term ,but The final approximate expression is:

[0044] .

[0045] This paper quantifies the attenuation factor of integral gain in synchronously generated signals. By normalizing the correlation function using pseudo-random codes, the attenuation effect of code phase deviation on the signal superposition amplitude is clarified. Residual frequency difference is introduced to reveal the impact of Doppler bias on the phase of the integral output. Furthermore, it concludes that the common phase term is eliminated in the covariance matrix solution, filling a gap in the integral model of synchronously generated signals. The clarification that the common phase term has no impact indicates that the coherent integration result does not introduce additional phase, providing a theoretical basis for the connection between integration and DOA estimation, and avoiding blind link design caused by the lack of clarity regarding the impact of integration on DOA estimation.

[0046] Step 106: Calculate the signal power based on the output signal after coherent integration, and calculate the output signal-to-noise ratio using the signal power and the pre-calculated noise power. Based on the output signal-to-noise ratio, derive the conclusion that the output signal-to-noise ratio in the synchronous signal generation scenario is linearly proportional to the coherent integration time.

[0047] The signal power is calculated based on the output signal after coherent integration:

[0048] ;

[0049] because For a non-dependent If the constant is , then we have:

[0050] ;

[0051] The output noise power is:

[0052] ;

[0053] Therefore, the output signal-to-noise ratio (SNR) is:

[0054] .

[0055] This demonstrates that even when multiple coherent signals coexist, coherent integration can still effectively amplify the total power of the entire signal mixture relative to the noise power, and the output signal-to-noise ratio is related to the coherent integration time. This relationship is linearly proportional. It provides a basis for predicting the performance of signal suppression accuracy in synchronous signal generation scenarios. Based on this quantitative relationship, the minimum integration time required can be deduced by setting the target output signal-to-noise ratio, or the improvement in signal-to-noise ratio can be estimated based on the upper limit of the integration delay allowed by the hardware. This avoids the decrease in real-time performance caused by excessively long integration time, or the insufficient gain caused by excessively short integration time.

[0056] Step 108: For asynchronous signal forwarding scenarios, based on the intermediate frequency signal expression, and taking into account the premise that the phase difference between any two signal codes is greater than one chip and the receiver obtains the phase and Doppler estimation values ​​of each signal code through multi-peak acquisition, independent and precisely aligned local copies are generated for the real signal and multiple forwarded signals respectively, and multiple local copy expressions are output.

[0057] In asynchronous signal relay scenarios, the difference between the phases of any two codes All are much larger than a chip width The receiver obtains the code phase and Doppler estimates of the three signals through multi-peak acquisition, i.e. Furthermore, three independent parallel tracking loops were established for each of these three signals. Unlike the synchronous signal generation scenario, the asynchronous signal relay scenario employs three different, precisely aligned local copies, each processing the same mixed input signal. Taking the first tracking loop as an example, the real satellite signal is extracted, and a local copy of the real signal is generated. for:

[0058] ;

[0059] Among them, the tracking loop will ensure and .

[0060] The requirement for the copy to be precisely aligned with the signal—with code phase and Doppler frequency shift matching—can be further deduced to determine the copy alignment accuracy requirements. This guides the parameter design of the receiver's multi-channel parallel processing module and prevents signal separation failure due to copy alignment errors.

[0061] Step 110: Calculate the correlation integral of the local copy and the conjugate of the mixed input signal. Simplify the integration result by taking advantage of the characteristic that the correlation value is close to zero when the code phase delay is greater than one chip. Based on the simplified integration result, derive the expression for the output signal-to-noise ratio in the asynchronous signal forwarding scenario, and conclude that the output signal-to-noise ratio is proportional to the input signal-to-noise ratio and the coherent integration time.

[0062] calculate Conjugate with a specific copy Relevant points:

[0063] ;

[0064] When the relative delay of the code phase is greater than one chip, the correlation value approaches zero. , The above formula can be simplified to:

[0065] ;

[0066] Similarly, , Therefore, the output signal-to-noise ratio is:

[0067] .

[0068] This indicates that in asynchronous signal forwarding scenarios, the output signal-to-noise ratio (SNR) is proportional to the input SNR and the coherent integration time. Effective signal separation and integral gain quantization are achieved in asynchronous signal forwarding scenarios. The simplified integration result is determined solely by the target signal. This demonstrates that a multi-replica plus multi-loop design can completely isolate asynchronous forwarding signals, providing theoretical support for the adaptability of the multi-peak acquisition-multi-loop tracking-coherent integration process in the receiver acquisition and tracking link, and avoiding incomplete suppression of spoofed signals due to improper process design.

[0069] The aforementioned method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals first acquires the intermediate frequency (IF) signal from the GNSS array receiver and generates a local copy that maximizes the total correlation energy. Then, by calculating the coherent integral output, introducing a pseudo-random code to normalize the correlation function, and simplifying the residual frequency difference, it clarifies the attenuation effects of code phase delay and Doppler frequency difference on signal amplitude. It also points out that the common phase term caused by the residual frequency difference is eliminated when solving the covariance matrix. This not only explains the mechanism of integral gain attenuation in synchronous signal generation but also clarifies that the coherent integral result has no negative impact on subsequent DOA estimation. It provides a theoretical basis for balancing the effects of integration time and parameter deviation in synchronous scenarios, avoiding gain loss caused by blindly setting the integration time. In synchronous scenarios, the signal power is calculated based on the integrated output signal, and the output signal-to-noise ratio (SNR) is obtained by combining it with a preset noise power, deriving a quantization relationship where the output SNR is linearly proportional to the coherent integration time. In asynchronous scenarios, similarly, through simplification of the integration result and SNR derivation, it is concluded that the output SNR is proportional to the input SNR and the coherent integration time. These two sets of quantitative relationships directly provide clear standards for the configuration of receiver integration time. Based on the lower limit of the required output signal-to-noise ratio (SNR) of the system, the minimum coherent integration time required can be deduced, or based on the upper limit of the allowable integration delay, the achievable SNR improvement can be determined, completely solving the problem of lacking a basis for parameter optimization in the background. Simultaneously, in asynchronous scenarios, based on the premise that the intermediate frequency signal expression and the code phase difference are greater than one chip, and multi-peak acquisition is used to obtain parameter estimates, an independent and precisely aligned local copy is generated for each signal. By calculating the correlation integral between the local copy and the mixed signal, effective separation of the real signal and the spoofed signal is achieved. Furthermore, the derived SNR expression is determined solely by the target signal input SNR and the integration time, providing theoretical support for the configuration of the number of tracking loops and the parameter alignment accuracy requirements in asynchronous scenarios, ensuring the rationality of the multi-channel parallel processing design. This application transforms ambiguous technical issues in the background art into quantifiable and applicable theoretical conclusions through differential analysis of synchronous and asynchronous GNSS signals in coherent integration. It directly provides precise guidance for the optimization of integration strategies, loop design, and parameter configuration of the acquisition and tracking link of GNSS array receivers, effectively improving the accuracy of spoofing signal suppression.

[0070] In one embodiment, based on the intermediate frequency signal and assuming that the code delay between the forged signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, a local copy that maximizes the total correlation energy is generated, including:

[0071] Based on the intermediate frequency signal and assuming that the code delay between the forged signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, the local replica that maximizes the total correlation energy is generated as follows:

[0072] ;

[0073] in, Indicates the code phase of the signal. It is a PRN code shared by all signals. This indicates the intermediate frequency (IF) of the GNSS signal. Indicates Doppler frequency shift, Indicates the time.

[0074] In one embodiment, calculating the coherent integral output based on the local copy and the intermediate frequency signal includes:

[0075] The coherent integral output is calculated based on the local copy and the intermediate frequency signal:

[0076] ;

[0077] in, Indicates the coherent integration time. Indicates the first The intermediate frequency signal received by each antenna element Indicates the conjugate of the local copy. Indicates the first Each signal component This indicates that the mean is 0 and the power is Additive white Gaussian noise.

[0078] In one embodiment, a pseudo-random code normalized correlation function and a residual frequency difference simplified coherent integral output are introduced to generate a coherently integrated output signal in a synchronous signal generation scenario, including:

[0079] By introducing a pseudo-random code normalized correlation function and a residual frequency difference simplified coherent integral output, the output signal after coherent integration in the synchronous signal generation scenario is generated as follows:

[0080] ;

[0081] in, They are the first The amplitude, data bits, code phase, and initial carrier phase of each signal. It is the first A signal at the antenna Spatial phase on, Indicates the code phase of the signal. This represents the time of coherent integration.

[0082] In one embodiment, calculating the signal power based on the output signal after coherent integration includes:

[0083] The signal power is calculated based on the output signal after coherent integration:

[0084] ;

[0085] in, This represents the total output signal after coherent integration.

[0086] In one embodiment, the pre-calculated noise power is:

[0087] ;

[0088] in, Indicates the coherent integration time. express The average value at any given time is 0, and the power is Additive white Gaussian noise, express The mean at time 0 is , and the power is Additive white Gaussian noise, express The conjugate of the local copy at any given moment, express A local copy at any time, Represents variance. This represents the noise integration time.

[0089] In one embodiment, the output signal-to-noise ratio is calculated using the signal power and a pre-calculated noise power, including:

[0090] The output signal-to-noise ratio is calculated using the signal power and the pre-calculated noise power as follows:

[0091] ;

[0092] in, Indicates signal power. Indicates noise power. For a non-dependent constant, Indicates power, This represents the time of coherent integration.

[0093] In one embodiment, for asynchronous signal forwarding scenarios, based on the intermediate frequency signal expression, and considering the premise that the phase difference between any two signal codes is greater than one chip and the receiver obtains the phase and Doppler estimation values ​​of each signal code through multi-peak acquisition, independent, precisely aligned local copies are generated for the real signal and multiple forwarded signals respectively, and multiple local copy expressions are output, including:

[0094] In asynchronous signal relay scenarios, the difference between the phases of any two codes Both are greater than one chip width The receiver obtains the code phase and Doppler estimates of the three signals through multi-peak acquisition, i.e. Furthermore, three independent parallel tracking loops were established for each of the three signals, using three different, precisely aligned local copies to process the same mixed input signal. Taking the first tracking loop as an example, the real satellite signal is extracted, and a local copy of the real signal is generated. for:

[0095] ;

[0096] Among them, the tracking loop will ensure and , This indicates the intermediate frequency (IF) of the GNSS signal. It is the Doppler frequency shift of the first signal. It is an estimate of the Doppler frequency shift of the first signal. This represents the code phase of the actual signal in the first tracking loop.

[0097] In one embodiment, the correlation integral of the local copy and the conjugate of the mixed input signal is calculated, and the integration result is simplified by utilizing the characteristic that the correlation value is close to zero when the code phase delay is greater than one chip, including:

[0098] The correlation integral between the local replica and the conjugate of the mixed input signal is calculated as follows:

[0099] ;

[0100] in, Indicates the coherent integration time. Indicates the first The intermediate frequency signal received by each antenna element Indicates the conjugate of a specific copy. Indicates the first Each signal component Represents the true signal. Represents a forwarding signal. This indicates that the mean is 0 and the power is Additive white Gaussian noise;

[0101] When the relative delay of the code phase is greater than one chip, the correlation value approaches zero. , The relevant integrals are simplified to:

[0102] ;

[0103] in, and This represents the amplitude and data bits of the actual signal. This indicates the actual signal at the antenna. Spatial phase on, This represents the initial carrier phase of the real signal. .

[0104] In one embodiment, the expression for the output signal-to-noise ratio in an asynchronous signal forwarding scenario is derived based on a simplified integration result, including:

[0105] Based on the simplified integration results, the expression for the output signal-to-noise ratio in asynchronous signal forwarding scenarios is derived as follows:

[0106] ;

[0107] in, Indicates signal power. Indicates noise power. They are the first The amplitude and data bits of each signal, Indicates the coherent integration time. For power, The input signal-to-noise ratio.

[0108] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0109] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for analyzing the coherent integral gain mechanism of synchronous and asynchronous GNSS signals, characterized in that, The method includes: For synchronous signal generation scenarios, the intermediate frequency signal received in the GNSS array receiver is obtained. Based on the intermediate frequency signal, and assuming that the code delay between the generated signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, a local copy that maximizes the total correlation energy is generated. The coherent integral output is calculated based on the local copy and the intermediate frequency signal. The pseudo-random code normalization correlation function and the residual frequency difference are introduced to simplify the coherent integral output, and the output signal after coherent integration in the synchronous signal generation scenario is generated. The signal power is calculated based on the output signal after coherent integration. The output signal-to-noise ratio is calculated using the signal power and the pre-calculated noise power. Based on the output signal-to-noise ratio, it is deduced that the output signal-to-noise ratio in the synchronous signal generation scenario is linearly proportional to the coherent integration time. For asynchronous signal forwarding scenarios, based on the intermediate frequency signal expression, and taking into account the premise that the phase difference between any two signal codes is greater than one chip and the receiver obtains the phase and Doppler estimation values ​​of each signal code through multi-peak acquisition, independent and precisely aligned local copies are generated for the real signal and multiple forwarded signals respectively, and multiple local copy expressions are output. The correlation integral between the local copy and the conjugate of the mixed input signal is calculated. The correlation value is simplified by taking advantage of the characteristic that the correlation value is close to zero when the code phase delay is greater than one chip. Based on the simplified integration result, the output signal-to-noise ratio expression in the asynchronous signal forwarding scenario is derived, and the conclusion is drawn that the output signal-to-noise ratio is proportional to the input signal-to-noise ratio and the coherent integration time. By introducing a pseudo-random code normalized correlation function and a residual frequency difference simplified coherent integral output, a coherently integrated output signal is generated for synchronous signal generation scenarios, including: By introducing a pseudo-random code normalized correlation function and a residual frequency difference simplified coherent integral output, the output signal after coherent integration in the synchronous signal generation scenario is generated as follows: ； in, They are the first The amplitude, data bits, code phase, and initial carrier phase of each signal. It is the first A signal at the antenna Spatial phase on, Indicates the code phase of the signal. Indicates the coherent integration time; The correlation integral between the local copy and the conjugate of the mixed input signal is calculated. The integral result is simplified by utilizing the characteristic that the correlation value approaches zero when the code phase delay is greater than one chip. This includes: The correlation integral between the local replica and the conjugate of the mixed input signal is calculated as follows: in, Indicates the coherent integration time. Indicates the first The intermediate frequency signal received by each antenna element Indicates the conjugate of a specific copy. Indicates the first Each signal component Represents the true signal. Represents a forwarding signal. This indicates that the mean is 0 and the power is Additive white Gaussian noise; When the relative delay of the code phase is greater than one chip, the correlation value approaches zero. , The relevant integral is simplified to: ； in, and This represents the amplitude and data bits of the actual signal. This indicates the actual signal at the antenna. Spatial phase on, This represents the initial carrier phase of the real signal. .

2. The method according to claim 1, characterized in that, Based on the intermediate frequency signal and assuming that the code delay between the generated signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, a local replica that maximizes the total correlation energy is generated, including: Based on the intermediate frequency signal and assuming that the code delay between the generated signal and the real signal is less than one chip and the coherence integration time is an integer multiple of the code period, the local replica that maximizes the total correlation energy is generated as follows: ； in, Indicates the code phase of the signal. It is a PRN code shared by all signals. This indicates the intermediate frequency (IF) of the GNSS signal. Indicates Doppler frequency shift, Indicates the time.

3. The method according to claim 1, characterized in that, Calculating the coherent integral output based on the local copy and the intermediate frequency signal includes: The coherent integral output is calculated based on the local copy and the intermediate frequency signal as follows: ； in, Indicates the coherent integration time. Indicates the first The intermediate frequency signal received by each antenna element Indicates the conjugate of the local copy. Indicates the first Each signal component This indicates that the mean is 0 and the power is Additive white Gaussian noise.

4. The method according to claim 1, characterized in that, Calculating the signal power based on the output signal after coherent integration includes: The signal power is calculated based on the output signal after coherent integration: ； make ; in, This represents the total output signal after coherent integration. They are the first The amplitude, data bits, code phase, and initial carrier phase of each signal. It is the first A signal at the antenna Spatial phase on, Indicates the code phase of the signal.

5. The method according to claim 4, characterized in that, The pre-calculated noise power includes: The pre-calculated noise power is: ； in, Indicates the coherent integration time. express The average value at any given time is 0, and the power is Additive white Gaussian noise, express The mean at time 0 is , and the power is Additive white Gaussian noise, express The conjugate of the local copy at any given moment, express A local copy at any time, Represents variance. This represents the noise integration time.

6. The method according to claim 5, characterized in that, The output signal-to-noise ratio is calculated using the signal power and the pre-calculated noise power, including: The output signal-to-noise ratio is calculated using the signal power and the pre-calculated noise power as follows: ； in, Indicates signal power. Indicates noise power. For a non-dependent constant, Indicates power, This represents the time of coherent integration.

7. The method according to claim 2, characterized in that, For asynchronous signal relay scenarios, based on the intermediate frequency signal expression and considering the premise that the phase difference between any two signal codes is greater than one chip, and that the receiver obtains the phase and Doppler estimates of each signal code through multi-peak acquisition, independent, precisely aligned local copies are generated for the real signal and multiple relayed signals, outputting multiple local copy expressions, including: In asynchronous signal relay scenarios, the difference between the phases of any two codes Both are greater than one chip width The receiver obtains the code phase and Doppler estimates of the three signals through multi-peak acquisition, i.e. Furthermore, three independent parallel tracking loops were established for each of the three signals, using three different, precisely aligned local copies to process the same mixed input signal. Taking the first tracking loop as an example, the real satellite signal is extracted, and a local copy of the real signal is generated. for: ； Among them, the tracking loop will ensure and , This indicates the intermediate frequency (IF) of the GNSS signal. It is the Doppler frequency shift of the first signal. It is an estimate of the Doppler frequency shift of the first signal. This represents the code phase of the actual signal in the first tracking loop.

8. The method according to claim 1, characterized in that, The expression for the output signal-to-noise ratio in asynchronous signal forwarding scenarios is derived based on simplified integration results, including: Based on the simplified integration results, the expression for the output signal-to-noise ratio in asynchronous signal forwarding scenarios is derived as follows: ； in, Indicates signal power. Indicates noise power. They are the first The amplitude and data bits of each signal, Indicates the coherent integration time. For power, The input signal-to-noise ratio.

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