A multi-threshold capture verification method and system based on the noise floor reference value

Abstract

The present invention belongs to the technical field of GNSS navigation receivers, and discloses a multi-threshold acquisition verification method and system based on a noise floor reference value. Two threshold values TH1 and TH2 are set, where TH1 > TH2. For a single acquisition verification process of a certain search unit, compare the quantity V to be detected with TH1. If V ≥ TH1, it is declared that the acquisition is successful and the acquisition process ends; if the quantity V to be detected < TH1, then judge the relationship between V and TH2; if V < TH2, it is judged as a noise unit; if the current search unit is the last search unit, it is declared that the captured satellite signal does not exist and the acquisition process ends, otherwise select the next search unit; if V is between TH1 and TH2, then calculate the relationship between the quantity V to be detected of the current search unit and the noise mean value, and adjust the acquisition verification parameters or counters to perform acquisition verification on this search unit. The present invention can accelerate the entire acquisition verification process.

Description

Technical Field

[0001] The present invention belongs to, but is not limited to, the technical field of GNSS navigation receivers, and particularly relates to a multi-threshold acquisition verification method and system based on a noise floor reference value. Background Art

[0002] The acquisition process of satellite signals by a GNSS navigation receiver includes several parts such as mixing, correlation operation, coherent integration / non-coherent integration, and decision-making, as Figure 1 shown. Among them, the decision-making device compares the detection quantity obtained from the previous operation with the decision threshold to determine whether the acquisition is successful this time. However, due to the existence of noise and interference, etc., the detection quantity on the search unit where the signal is located is sometimes weakened, while the detection quantity on other search units sometimes shows a peak value, resulting in missed detection or false alarm phenomena. Therefore, after the navigation receiver determines success on a search unit, it should not immediately transfer from the acquisition state to the next state, but should continue to further confirm this unit.

[0003] The general acquisition verification strategy generally adopts the mode as Figure 2 shown: The steps are to first compare the quantity to be detected with the threshold value, then adjust the parameters or counters set in the acquisition verification process according to the comparison result, such as performing addition or subtraction operations on the parameters or counters, and finally, according to the adjusted parameter or counter value, feedback the verification result. The feedback results include: successful acquisition and end of acquisition on this search unit, failed acquisition on this search unit and determination of whether to search the next unit, and not yet ending the verification and continuing to perform acquisition verification on this search unit.

[0004] The acquisition verification algorithms of navigation receivers can usually be divided into two types: the fixed search time method and the variable search time method. The fixed search time method means that the receiver searches a preset fixed time on each search unit in total, and then makes a judgment on whether the acquisition is successful based on the multiple search results of the search unit within this time period. Its representative algorithm is the N-out-of-M algorithm; while the variable search time method means that the receiver may search for unequal times on each search unit according to certain rules and in combination with the detection situation at that time. Its representative algorithm is the Tong algorithm. The following details these two representative detection strategies.

[0005] 1. The N-out-of-M acquisition strategy, that is, the N-out-of-M strategy

[0006] The N-out-of-M strategy: Search a search unit N times. For a single decision, if the quantity to be detected V exceeds the threshold, the value of the counter m is incremented by 1. If N searches have been completed and the number of successful times is not less than M, it is considered that the acquisition is successful in this frequency range; otherwise, the acquisition fails. Its process is as Figure 3 shown.

[0007] 2. Tong Capture Search Detection Method

[0008] The Tong search detection method is a linear search method with a variable search time. In principle, it adds more search time to those search units where it is difficult to determine whether the signal has been successfully captured. Its process is as follows Figure 4 shown. It includes a counting variable K, as well as a threshold A of the counting variable K and an initial value of the counting variable K. First, when the receiver starts to search for a signal in a certain search unit, the value of the counting variable K is first preset to B; then, after each integration of the signal ends, the algorithm compares the quantity V to be detected with the capture threshold value TH to decide whether to continue the search for the current search unit. Compared with 0 and the threshold value A, the value of K will show the following three situations: one is that the value of K is greater than 0 but less than A, in which case the receiver needs to stay and add one more search for the current search unit; the second is that the value of K is equal to A, in which case the algorithm believes that the receiver has successfully captured the signal in the current search unit, and the two-dimensional search ends accordingly; the third is that the value of K is equal to 0, in which case the receiver should abandon the search for the current search unit and move to the next search unit to continue the search process as follows Figure 4 shown.

[0009] The technical problems that urgently need to be solved in the existing technology are as follows: In the case of a low carrier-to-noise ratio, especially when the single-detection probability is close to 0.5, the value of K will oscillate repeatedly between adding 1 and subtracting 1 in the Tong search detection method. Therefore, the number of detections is large and the computational complexity increases greatly. The N-out-of-M search detection strategy is a detection strategy with a fixed number of searches. Therefore, its detection performance is worse than that of the Tong search detection strategy with a variable search time. Since the satellite signal capture search detection strategy greatly affects the first positioning time of the receiver, a better signal capture search detection strategy should have less dwell time. However, the time performance of the above two traditional detection strategies is not very ideal, with a large number of detections and a long capture time. Moreover, if a capture unit is determined to be a noise unit, then the quantity to be detected of it will be directly discarded, and then go to search for other capture units, and the previous quantity to be detected cannot be utilized. Therefore, there is an urgent need for a new signal capture search detection strategy. Summary of the Invention

[0010] Aiming at the problems existing in the existing technology, the present invention provides a multi-threshold capture verification method and system based on a noise floor reference value.

[0011] The present invention is implemented as follows. A multi-threshold capture verification method based on a noise floor reference value includes: S1, setting a first threshold value TH1 and a second threshold value TH2, and satisfying TH1 > TH2; S2, during a capture verification process of a certain search unit, for the quantity V to be detected in the search unit, first determine whether V is greater than or equal to TH1. If satisfied, it is considered that the signal in this search unit is strong enough, declare successful capture, and end the capture process; S3, if V is less than TH1, then further determine whether V is less than TH2. If satisfied, it is considered that the signal in this search unit is weak enough, and it is determined as a noise unit. If the current search unit is the last search unit, declare that the captured satellite signal does not exist, and end the capture process. Otherwise, select the next search unit; S4, if V is between TH1 and TH2, it is considered that the current search unit may be a signal unit, and it is necessary to calculate the relationship between the quantity V to be detected in the current search unit and the noise mean value and based on the calculation result, adjust the capture verification parameters or counter, and perform capture verification on this search unit.

[0012] Furthermore, the calculation of the noise mean value includes: taking the values of the quantities to be detected of multiple search units determined as noise; accumulating the values of the quantities to be detected, and calculating the geometric mean value.

[0013] Furthermore, in S4, the method for calculating the relationship between the quantity V to be detected and the noise mean value includes: calculating the ratio of the two; calculating the difference between the two; and performing signal evaluation based on the ratio R or the difference Δ.

[0014] Furthermore, the adjustment of the capture verification parameters or counter of the search unit includes: if the ratio R or the difference Δ exceeds a preset threshold, increase the capture confidence of this search unit and increase the cumulative counter value; if the ratio R or the difference Δ is lower than the preset threshold, decrease the capture confidence of this search unit and decrease the cumulative counter value.

[0015] Furthermore, the first threshold value TH1 and the second threshold value TH2 can be dynamically adjusted according to historical detection data, where: if the quantities V to be detected of multiple search units are lower than TH1 but between TH2 and TH1, then decrease TH1 to improve the capture sensitivity;

[0016] if the noise mean value rises significantly, then increase TH2 to reduce the probability of misjudging noise as a weak signal.

[0017] Furthermore, the method also includes readjusting the search strategy when capture fails, where: record the quantities V to be detected of all the detected search units, and calculate the maximum value V max ; if Vmax If it is between TH2 and TH1, it is taken as the new threshold, and the capture verification is re-executed.

[0018] Another object of the present invention is to provide a multi-threshold capture verification system based on a noise floor reference value for a multi-threshold capture verification method based on a noise floor reference value. The system includes: a signal detection module for obtaining a quantity to be detected of a search unit and comparing it with a set first threshold and a second threshold; a noise analysis module for calculating a noise mean value of a plurality of noise units and updating the noise reference value in real time; a signal evaluation module for evaluating the quantity to be detected between the first threshold and the second threshold and adjusting the capture strategy according to the relationship between the quantity to be detected and the noise mean value; a dynamic adjustment module for dynamically adjusting the first threshold and the second threshold according to the detection result of the search unit to adapt to different signal environments.

[0019] Further, the signal detection module includes: a comparison unit for sequentially determining whether the quantity to be detected is greater than or equal to the first threshold, and if satisfied, determining that the capture is successful; a noise screening unit for determining whether the quantity to be detected is lower than the second threshold, and if satisfied, determining it as a noise unit and deciding whether to continue searching for the next unit.

[0020] Further, the noise analysis module includes: a data storage unit for storing the quantity to be detected data of a plurality of noise units; a mean value calculation unit for calculating the noise mean value of the noise units and updating the noise reference value; a dynamic update unit for continuously calculating and adjusting the noise mean value during the operation of the system to adapt to changes in the signal environment.

[0021] Further, the dynamic adjustment module includes: a threshold adjustment unit for adjusting the first threshold and the second threshold according to historical search data to optimize signal capture; an adaptive parameter unit for performing real-time adjustment of the capture parameters based on the signal evaluation result; a capture strategy optimization unit for dynamically optimizing the capture strategy according to the feedback result of the signal evaluation module to improve the accuracy and stability of signal detection.

[0022] Another object of the present invention is to provide a computer device. The computer device includes a memory and a processor. When a computer program stored in the memory is executed by the processor, the processor executes the steps of the multi-threshold capture verification method based on a noise floor reference value.

[0023] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the multi-threshold capture verification method based on a noise floor reference value.

[0024] Another object of the present invention is to provide an information data processing terminal, which includes the multi-threshold capture verification system based on the noise floor reference value described above.

[0025] Combined with the above technical solutions and the solved technical problems, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows: First, compared with the prior art, the multi-threshold capture verification strategy based on the noise floor reference value proposed by the present invention has the following advantages: 1. By setting multiple thresholds, the present invention can end the search and verification process for stronger or weaker signal units more quickly; 2. In the prior art, if a capture unit is determined to be a noise unit, its quantity to be detected will be directly discarded, and then other capture units will be searched. The strategy proposed by the present invention can make full use of the quantity to be detected of each search unit, calculate the noise amplitude or energy mean value by using the quantity to be detected value of the unit determined to be a noise unit, and then use it to evaluate the signals of the subsequent capture units; 3. In the prior art, in each search process, the update adjustment step size of the verification parameter or counter is generally 1, that is, it increases or decreases by 1 each time. The strategy proposed by the present invention can judge the strength of the current signal according to the relationship between the quantity to be detected in the current search unit and the noise mean value, and then accelerate the update adjustment of the verification parameter or counter step size. Thus, while minimizing the probability of missed detection as much as possible, the entire capture verification process is accelerated.

[0026] Second, when the technical solution of the present invention is applied to a satellite navigation receiver, it can effectively improve the speed of capturing satellites while taking into account false alarms and missed detections, and shorten the first positioning speed and the time of loss-of-lock and repositioning of the satellite navigation receiver. Especially in areas such as urban valleys, satellite signals are frequently blocked by overpasses, tunnels, mountains, and trees. The receiver will perform frequent loss-of-lock and repositioning. The time of loss-of-lock and repositioning is very intuitive and profound for the user experience. Quick repositioning is an important factor in the performance of the satellite navigation receiver. The present invention shortens the first positioning and repositioning times, making the receiver module more commercially competitive.

[0027] The technical solution of the present invention solves the contradiction between false alarms and missed detections and the capture speed. Missed detections will reduce the available satellites and may lead to failure to capture satellites. False alarms will lead to subsequent positioning errors. In order to reduce false alarms and missed detections, the capture results need to be captured and confirmed multiple times. Multiple captures and confirmations result in a slow speed of obtaining the capture results and ultimately a slow positioning speed. In addition to affecting the first positioning, it may also cause the loss-of-lock and repositioning time index to be unqualified. The repositioning time is directly intuitive to the user experience and greatly affects the user experience and the selection of the solution.

[0028] The present invention solves this contradiction, quickly eliminates the noise detection unit to detect useful signals, and realizes capturing satellite signals more quickly while taking into account false alarms and missed detections, and shortens the positioning time. Description of the Drawings

[0029] Figure 1 is the principle block diagram of navigation signal acquisition provided by the prior art; Figure 2 is the general acquisition verification strategy flowchart provided by the prior art; Figure 3 is the schematic diagram of the N-of-M acquisition search detection method provided by the prior art; Figure 4 is the schematic diagram of the Tong acquisition search detection method provided by the prior art; Figure 5 is the step block diagram of the multi-threshold acquisition verification strategy based on the noise floor reference value provided by the embodiment of the present invention; Figure 6 is the flowchart of the multi-threshold acquisition verification strategy based on the noise floor reference value provided by the embodiment of the present invention; Figure 7 is the schematic diagram of the method for updating the noise mean provided by the embodiment of the present invention; Figure 8 is the schematic diagram of Application Scenario 1 of the multi-threshold acquisition verification strategy based on the noise floor reference value provided by the embodiment of the present invention; Figure 9 is the schematic diagram of Application Scenario 2 of the multi-threshold acquisition verification strategy based on the noise floor reference value provided by the embodiment of the present invention; Figure 10 is the system structure diagram of the multi-threshold acquisition verification system based on the noise floor reference value provided by the embodiment of the present invention; Figure 11 is the time schematic diagram of the measured acquisition time consumption provided by the embodiment of the present invention; Figure 12 is the schematic diagram of the acquisition success probability provided by the embodiment of the present invention; Figure 13 is the schematic diagram of the acquisition false alarm probability provided by the embodiment of the present invention. Detailed implementation manners

[0030] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0031] The multi-threshold acquisition verification method based on the noise floor reference value provided by the embodiment of the present invention uses two threshold values, namely the first threshold and the second threshold, to screen the quantity to be detected of the search unit. Among them, the first threshold is relatively high and is only used to identify strong signals, while the second threshold is relatively low and is used to eliminate noise units. Through this dual-threshold mechanism, misacquisition can be reduced and the signal recognition accuracy of the system can be improved.

[0032] (1) Signal acquisition process and threshold determination

[0033] The first step: Determine whether the quantity to be detected exceeds the first threshold; if the quantity to be detected is greater than or equal to the first threshold, the search unit is directly determined to have successfully captured the signal, and the acquisition process ends.

[0034] Step 2: Determine whether the quantity to be detected is lower than the second threshold; if the quantity to be detected is lower than the second threshold, then this search unit is determined to be a pure noise unit: if this search unit is the last unit within the current search range, then it is considered that no signal has been captured and the capture process ends. If this search unit is not the last unit, then continue to search the next unit.

[0035] Step 3: If the quantity to be detected is between the two thresholds, then conduct further evaluation; it is necessary to calculate the relationship between this quantity to be detected and the current noise mean value to decide whether to adjust the capture strategy or conduct further signal confirmation.

[0036] (2) Noise Mean Calculation and Dynamic Adjustment

[0037] Calculate the noise mean value among multiple search units and conduct dynamic adjustment. The calculation method is as follows: Take the quantity-to-be-detected values of multiple search units determined to be noise, add them up and then divide by the number of units to obtain the noise mean value. Another method is to use the geometric mean value to reduce the influence of abnormal data on the noise mean value and improve the calculation stability. This noise mean value is used for signal evaluation of subsequent search units and can be dynamically updated over time to adapt to different signal environments.

[0038] (3) Signal Evaluation and Adaptive Capture Verification

[0039] If the quantity to be detected of a certain search unit is between the two thresholds, then there may be a signal in this unit and it is necessary to evaluate its signal strength. By calculating the ratio of the quantity to be detected to the noise mean value, if the ratio is large, it indicates that the signal is strong and the capture strategy can be adjusted to enhance the sensitivity. By calculating the difference between the quantity to be detected and the noise mean value, if the difference is large, there may be a signal and the counter can be incremented to accumulate signal information and improve the capture accuracy. Based on the evaluation results, the system can dynamically adjust the capture parameters, such as reducing the first threshold to increase the sensitivity, or increasing the second threshold to reduce the noise misjudgment.

[0040] (4) Dynamically Adjust the Capture Strategy

[0041] Since the signal environment may change, an adaptive threshold adjustment mechanism is adopted: if the quantity to be detected of multiple search units is lower than the first threshold but close to it, then the first threshold can be appropriately reduced to improve the capture ability of weak signals. If the noise mean value increases significantly, then the second threshold can be appropriately increased to reduce the situation where noise units are misjudged as signals.

[0042] (5) Overall System Process and Advantages

[0043] This method improves the accuracy of signal acquisition and reduces the calculation error through high and low dual-threshold screening, combined with noise mean calculation and dynamic adjustment. Compared with the single-threshold method, this method reduces the false detection rate, improves the acquisition ability for weak signals, and can adapt to different noise environments, enabling the system to perform signal search and confirmation more efficiently.

[0044] The block diagram of the multi-threshold acquisition verification strategy based on the noise floor reference value proposed by the present invention is as Figure 5 shown, and the part marked by the dotted line is the core point of the present invention.

[0045] The flow chart of the multi-threshold acquisition verification strategy based on the noise floor reference value proposed by the present invention is as Figure 6 shown. Two thresholds are set: the first detection threshold and the second detection threshold. Among them, the first detection threshold is larger. If the quantity to be detected exceeds the first detection threshold, it can be considered that a signal has been successfully acquired on this search unit. The second detection threshold is smaller. If the quantity to be detected is less than the second detection threshold, the current search unit can be considered as noise, and whether to start searching the next search unit is selected according to whether it is the last unit currently. In addition, the quantity to be detected needs to be superimposed with the quantity to be detected that was previously determined as noise, and the noise amplitude or energy mean is calculated. In both of the above cases, only one search of the current search unit is required to confirm the search result. If the current quantity to be detected is between the highest threshold and the lowest threshold, it can be determined that the signal may be acquired on this search unit, and this search unit needs to be further verified. The signal is evaluated according to the relationship between the detection quantity value of the current search unit and the noise mean, and then according to the evaluation result, the acquisition verification parameters or counters are adjusted to perform acquisition verification on the current search unit.

[0046] Specifically, the method for calculating the noise mean and the method for evaluating the signal according to the relationship between the detection quantity value of the current search unit and the noise mean are described as follows: 1. Noise mean calculation: The quantities to be detected of each unit determined as noise are accumulated and then the geometric mean is calculated. 2. The method for evaluating the current signal: The purpose is to evaluate the relationship between the quantity to be detected in the current search unit and the noise mean. The calculation method can be the ratio or the difference between the two.

[0047] In addition, it should be noted that different calculation methods for evaluating the relationship between the quantity to be detected in the current search unit and the noise mean will correspond to different verification parameter or counter adjustment strategies.

[0048] The following details the practical application of the multi-threshold acquisition verification strategy based on the noise floor reference value proposed by the invention.

[0049] Assume that the quantity to be detected is the signal amplitude. First, set two threshold values TH1 and TH2. Among them, TH1 > TH2, and the selection of their values can be based on test calibration or empirical values, which will not be elaborated here. The requirement for them is that TH1 must be large enough and TH2 must be small enough.

[0050] For a single capture verification process of a certain search unit, first compare the magnitude of the quantity to be detected V with the threshold TH1. If V ≥ TH1, it is considered that the signal in this search unit is strong enough, and the capture can be declared successful and the capture process ends; if the quantity to be detected V < TH1, then further judge the relationship between V and TH2. If V < TH2, it is considered that the signal in this search unit is weak enough and can be judged as a noise unit. At this time, if the current search unit is already the last search unit, it is declared that the captured satellite signal does not exist and the capture process ends, otherwise the next search unit is selected. In addition, the quantity to be detected that is currently judged as noise will also be used to update the noise mean value, and the specific calculation method is as Figure 7 shown.

[0051] Otherwise, if the quantity to be detected V < TH1 and if V ≥ TH2, it is considered that the current search unit may be a signal unit. It is necessary to evaluate the relationship between the quantity to be detected in the current search unit and the noise mean value. Here, the method of calculating the ratio is used as an example to calculate how many times the quantity to be detected in the current search unit is more than the noise mean value, that is, calculate R = (V / V noise ) - 1, where V noise is the statistically calculated noise mean value. After obtaining this R value, it can be directly or indirectly used to adjust the capture verification parameters or counters. The following combines the previously mentioned Tong capture search detection strategy and N out of M capture search detection strategy, and the examples are as follows: A. Application scenario 1 of the multi-threshold capture verification strategy based on the noise floor reference value. Combining the Tong search verification method, after calculating the R value, according to the size of the R value, the value of the counter K can be directly adjusted. As shown in the example in Figure 8 , if R ≥ 1, it means that the quantity to be detected in the current search unit is greater than or equal to 2 times the noise mean value. At this time, the value of K can be adjusted according to the actual application, such as increasing the value of K by R to accelerate the capture verification process; conversely, if R < 1, it means that the quantity to be detected in the current search unit is less than 2 times the noise mean value. At this time, the value of K can be adjusted according to the actual application, such as keeping the value of K unchanged, or directly subtracting 1 from the value of K or other numbers related to R. B. Application scenario 2 of the multi-threshold capture verification strategy based on the noise floor reference value. Combining the N out of M search verification method, after calculating the R value, according to the size of the R value, the values of the counters A and B can be directly adjusted. As shown in Figure 9As shown in the example in , if R≥1, it indicates that the quantity to be detected in the current search unit is greater than or equal to twice the noise mean. At this time, the values of A and B can be adjusted according to the actual application. For example, both the values of A and B can be increased by R to accelerate the capture verification process. On the contrary, if R<1, it indicates that the quantity to be detected in the current search unit is less than twice the noise mean. At this time, the values of A and B can be adjusted according to the actual application. For example, the values of A and B can be kept unchanged, or the values of A and B can be directly decreased by 1 or other numbers related to R.

[0052] As Figure 10 shown, the multi-threshold capture verification system based on the noise floor reference value includes: a detection quantity calculation module for calculating the detection quantity; a multi-threshold comparator for comparing the detection quantity with the set detection threshold; a noise floor calculator for calculating the noise mean; a signal strength evaluation module for evaluating the signal strength of the current search unit; a parameter verification module for performing parameter verification or counter adjustment; and a result feedback module for feeding back the output result.

[0053] The system obtains the quantity to be detected of the search unit through the detection quantity calculation module and uses the multi-threshold comparator to compare it with the set first threshold and second threshold. The first threshold is used to identify strong signals. If the quantity to be detected is greater than or equal to this threshold, it can be directly determined that the signal capture is successful and the further search is terminated. The second threshold is used to eliminate noise. If the quantity to be detected is less than this threshold, it can be determined that this unit is a pure noise unit and a decision is made on whether to continue searching the next unit. At the same time, the noise floor calculator is responsible for storing the data of multiple noise units and calculating the noise mean to provide a reference value for subsequent signal evaluation.

[0054] For the quantity to be detected between the two thresholds, the system does not immediately determine whether it contains a signal, but hands it over to the signal strength evaluation module for further analysis. The evaluation methods include calculating the ratio or difference between the quantity to be detected and the noise mean to judge the degree of its deviation from the noise level. If the quantity to be detected is much higher than the noise mean, it indicates a higher possibility of the existence of a signal. If the quantity to be detected is close to the noise mean, it may still belong to noise and further verification is required. This multi-level judgment mechanism effectively improves the detection accuracy of the system and reduces the probability of false detection and missed detection.

[0055] Due to possible changes in the signal environment, the system is equipped with a parameter verification module that can dynamically adjust the threshold value or modify the counter parameters based on the signal evaluation results. For example, when the detection values of multiple search units are lower than the first threshold but close to it, the system can lower the first threshold to improve the capture ability of weak signals; when there is a significant fluctuation in the noise mean, the system can adjust the second threshold to avoid misjudging noise as a signal. In addition, this module can also optimize the counter strategy. If a certain search unit detects a suspected signal continuously for multiple times, the counting weight can be increased to improve the reliability of signal confirmation.

[0056] The system includes a result feedback module that can feedback the finally determined signal capture result to the control center or the upper-layer application to enable it to adjust subsequent operations. This method can be integrated into a computer device, where the computer device includes a memory and a processor. The memory stores a computer program, and when the program is executed by the processor, the entire multi-threshold capture verification process can be realized. In addition, this method can also be stored in a computer-readable storage medium or applied to an information data processing terminal to enable it to have the intelligent signal capture ability and improve the signal processing efficiency in a complex environment.

[0057] Evidence related to the technical effects obtained in the embodiments of the present invention.

[0058] Experimental conditions: This solution combines the M-out-of-N scheme, where M is set to 5, N is set to 4, the first threshold V1 is set to 8, the second threshold V2 is set to 4, and the Beidou B3 signal is captured. The signal strength ranges from -145 dBm to -125 dBm. The measured capture time consumed is as Figure 11 shown. The capture success probability and false alarm probability are statistically counted as Figure 12 and Figure 13 shown.

[0059] In the M-out-of-N algorithm of the present invention, while maintaining the capture probability and false alarm probability to be basically equivalent, the capture time of the M-out-of-N scheme is fixed, and the capture time of the present invention is effectively shortened.

[0060] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those of ordinary skill in the art can understand that the above-mentioned devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and their modules of the present invention can be implemented by hardware circuits of programmable hardware devices such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above hardware circuits and software such as firmware.

[0061] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A multi-threshold capture verification method based on a noise floor reference value, characterized in that, The method includes the following steps: Step 1, set a first threshold TH1 and a second threshold TH2, and satisfy TH1 > TH2; Step 2, for the quantity V to be detected of the search unit, first determine whether V is greater than or equal to TH1. If satisfied, declare that the capture is successful and end the capture process; Step 3, if V is less than TH1, then determine whether V is less than TH2. If satisfied, it is determined as a noise unit. If this unit is the last search unit, declare that no signal is captured. Otherwise, select the next search unit; Step 4, if V is between TH1 and TH2, then calculate the relationship between the quantity V to be detected of the current search unit and the noise mean value and adjust the capture verification parameter or counter based on the calculation result to perform capture verification on this search unit; The calculation of the noise mean value includes: taking the quantity values to be detected of multiple search units determined to be noise; accumulating the quantity values to be detected and calculating the geometric mean value; In Step 4, the method for calculating the relationship between the quantity V to be detected and the noise mean value includes: calculating their ratio ; calculating their difference ; performing signal evaluation based on the ratio R or the difference Δ.

2. The multi-threshold capture verification method based on the noise floor reference value according to claim 1, wherein The adjustment of the capture verification parameter or counter of the search unit includes: if the ratio R or the difference Δ exceeds the preset threshold, increasing the capture confidence of the search unit and increasing the cumulative counter value; if the ratio R or the difference Δ is lower than the preset threshold, decreasing the capture confidence of the search unit and decreasing the cumulative counter value.

3. The multi-threshold capture verification method based on the noise floor reference value according to claim 1, wherein The first threshold TH1 and the second threshold TH2 are dynamically adjusted according to historical detection data, where: if the quantity to be detected V of multiple search units is lower than TH1 but between TH2 and TH1, then TH1 is decreased to improve the capture sensitivity; if the noise mean rises significantly, then TH2 is increased to reduce the probability of misjudging noise as a weak signal.

4. The multi-threshold capture verification method based on the noise floor reference value according to claim 1, wherein The method further includes readjusting a search strategy when a capture fails, wherein: recording a quantity V to be detected for all detected search units, and calculating a maximum value V max ; if V max is between TH2 and TH1, then using it as a new threshold and re-performing capture verification.

5. A multi-threshold capture verification system based on a noise floor reference value for the method according to any one of claims 1 to 4, characterized in that, The system includes: a signal detection module for obtaining the quantity to be detected of the search unit and comparing it with a set first threshold and second threshold; a noise analysis module for calculating the noise mean of multiple noise units and updating the noise reference value in real time; a signal evaluation module for evaluating the quantity to be detected between the first threshold and the second threshold and adjusting the capture strategy according to the relationship between the quantity to be detected and the noise mean; a dynamic adjustment module for dynamically adjusting the first threshold and the second threshold according to the detection result of the search unit to adapt to different signal environments.

6. The multi-threshold capture verification system based on the noise floor reference value according to claim 5, wherein The signal detection module includes: a comparison unit for sequentially determining whether the quantity to be detected is greater than or equal to the first threshold, and if satisfied, determining that the capture is successful; a noise screening unit for determining whether the quantity to be detected is lower than the second threshold, and if satisfied, determining it as a noise unit and deciding whether to continue searching for the next unit.

7. The multi-threshold capture verification system based on the noise floor reference value according to claim 5, wherein The noise analysis module includes: a data storage unit for storing the data of the quantity to be detected of multiple noise units; a mean calculation unit for calculating the noise mean of the noise units and updating the noise reference value; a dynamic update unit for continuously calculating and adjusting the noise mean during the operation of the system to adapt to the change of the signal environment.

8. The multi-threshold capture verification system based on a noise floor reference value according to claim 5, characterized in that, The dynamic adjustment module includes: a threshold adjustment unit for adjusting the first threshold and the second threshold according to the historical search data to optimize the signal capture; an adaptive parameter unit for performing real-time adjustment of the capture parameters based on the signal evaluation result; a capture strategy optimization unit for dynamically optimizing the capture strategy according to the feedback result of the signal evaluation module to improve the accuracy and stability of signal detection.

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