Setting signal detection thresholds

Abstract

And setting a signal detection threshold value. A method and apparatus for setting a signal detection threshold are provided. The noise level, the number of search intervals, and the integration time are used to calculate the average and standard deviation of the maximum interval values. The signal detection threshold may then be set to a predetermined number of standard deviations from the maximum interval value.

Description

Technical Field

[0001] The present invention relates to a navigation satellite system (NSS), including a global navigation satellite system (GNSS) and a regional navigation satellite system, and more particularly to a method for setting a detection threshold in a signal acquisition process. Background Art

[0002] The technology used for GNSS positioning is well known in the art. Existing NSS include Global Positioning System (GPS), Galileo, GLONASS, QZSS and NAVIC and BeiDou Navigation Satellite System (BDS) (also referred to as "BeiDou" in this article). Each GNSS includes a satellite constellation, also referred to as a "space vehicle" (SV) in the art, which orbits the earth. Typically, each SV sends multiple satellite signals. These signals are received by a GNSS receiver that expects to calculate its position. The GNSS receiver can use the signal to perform multiple ranging measurements to derive information about the distance between the receiver and the corresponding satellite. When a sufficient number of measurements can be made, the position of the receiver can then be calculated by multi-point positioning.

[0003] Although the NSS spacecraft transmits a signal at a predetermined frequency, the frequency received by the antenna may be different from the transmitted frequency due to Doppler shift and / or unknown receiver clock drift. Therefore, a range of Doppler frequencies must be searched in order to identify the signal. In addition, in order to identify the signal, a known code specific to the satellite is used. However, the time delay of the code is unknown, so a range of code delays must be tried or compared to identify the signal. Therefore, a range of frequencies over the range of code delays must be searched in order to identify or acquire the signal. This generates a 2D search space of correlation values ​​calculated for different combinations of Doppler shift and code delay. A high correlation value for a specific Doppler frequency and code delay combination can indicate a signal.

[0004] However, for each frequency shift and code delay combination, there is noise and a threshold must be set above which the signal is considered recognized. If the signal threshold is too high, the signal may be lost. However, if the signal threshold is set too low, there may be too many false positives.

[0005] The signal threshold for optimal detection varies with the integration time. In addition, the threshold varies depending on the size of the search space. A commonly used approach is to maintain a lookup table for signal thresholds for search spaces of different sizes and different integration times. However, this requires storing a large number of lookup tables, which is very inefficient and takes up a lot of memory. Summary of the invention

[0006] It is desirable to acquire the signal as efficiently and accurately as possible and to reduce false positive detections of the signal.

[0007] According to one aspect, a signal acquisition method in a navigation satellite system is provided, the method setting a signal detection threshold for detecting a signal over a frequency range and a code delay range, the frequency and code delay range being divided into search intervals, each search interval having a frequency and a code delay, the method comprising: determining noise in a plurality of search intervals, determining a standard deviation of noise in a single search interval among the plurality of search intervals, determining an integration time t, determining the number of search intervals n, calculating an expected noise and an expected standard deviation of a search interval having maximum noise based on the number of search intervals and the standard deviation of noise in a single search interval, calculating a signal detection threshold based on a plurality of standard deviations from the expected noise of the search interval having maximum noise, and setting the signal detection threshold.

[0008] By calculating the signal detection threshold, the need for a very large lookup table is eliminated. Advantageously, the signal detection threshold is calculated based on a particular search space and the associated expected noise level. Since the expected maximum noise level is calculated specifically for the search space used, false alarms are minimized and signals are detected more consistently.

[0009] By setting the signal detection threshold based on the expected maximum noise value for a search space of relevant size, there is a consistent false alarm rate regardless of the size of the search space. If the search space changes, the signal detection threshold can be recalculated to maintain a consistent false alarm rate.

[0010] The method of the present invention is particularly useful in systems where limited computing power and memory exist, as it reduces the requirement for cumbersome look-up tables.

[0011] Optionally, the method further comprises detecting a signal level in each search interval; and identifying one or more signals above a signal detection threshold.

[0012] The signal level in each interval is compared to a signal detection threshold, and once a signal level above the signal detection threshold is detected, it may no longer be necessary to compare the signal level in further intervals to the signal detection threshold because the signal has already been identified. This in turn saves computational resources in the system.

[0013] The frequency of the identified signal may be determined, and the code delay of the identified signal may also be determined.The identified signal may then be tracked using known tracking mechanisms.

[0014] Alternatively, the pseudorange of the satellite transmitting the signal may be determined. Using multiple pseudoranges from multiple different satellites, a position fix may also be determined. This may be summarized as a position, velocity, time "PVT" fix.

[0015] Determining the noise may optionally include correlating the signal in the interval with a predetermined code. The code may be a random code, or may be, for example, all ones or all zeros. Determining the noise in a plurality of search intervals may include determining the noise in all search intervals.

[0016] The average noise per search interval (where c is the code length) is The expected noise for a search interval with integration time t=m and maximum noise is given by: Gumbel =b n +a n γ, where γ is the Euler-Mascheroni constant, and and And the variance of the noise in the search interval with the maximum noise is

[0017] Optionally, the method may further include setting a second signal detection threshold on a second frequency range different from the first frequency range and a second code delay range different from the first code delay range, the method further includes: setting a plurality of second frequency intervals, setting a plurality of second code delay intervals, determining the noise in a plurality of search intervals, determining the standard deviation of the noise of a single search interval in the plurality of search intervals, determining an integration time t, determining the number of search intervals n, calculating the expected noise and the expected standard deviation of the search interval with the maximum noise based on the number of search intervals and the standard deviation of the noise of the single search interval, calculating the second signal detection threshold based on a plurality of standard deviations from the maximum noise signal, and setting the second signal detection threshold. The second signal detection threshold may be different from the initial signal detection threshold.

[0018] The second signal detection threshold may be set to the same number of standard deviations from the maximum expected noise signal as the initial signal detection threshold was set. Advantageously, this will maintain a constant error rate.

[0019] The second frequency range may be a smaller frequency range and include the frequencies and code delays of the detected signal. Thus, when the signal is initially detected, a smaller search area may be defined and the frequencies and code delays of the signal may be detected at a higher granularity.

[0020] Once the second frequency threshold has been set, the signal level in each interval may be detected and one or more signals above the signal detection threshold identified. The frequency and code delay of the identified signal may be determined.

[0021] According to the present invention, there is provided a computer program comprising computer program code configured to cause one or more physical computing devices to perform all the steps of the method of any one of the preceding claims when the computer program is run on the one or more physical computing devices.

[0022] According to the present invention, a global navigation satellite system (hereinafter referred to as GNSS) receiver (100) is provided, which is configured to set a signal detection threshold for detecting a signal, and the GNSS receiver includes a processor configured to execute the steps as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0024] Figure 1 is a schematic block diagram of a GNSS receiver according to an example;

[0025] Figure 2 is a receiver structure for parallel acquisition and signal processing;

[0026] Figure 3 is a flow chart illustrating the method of the present invention;

[0027] Figure 4 is a flow chart illustrating a noise determination method;

[0028] Figure 5 is a flow chart illustrating an alternative method of the present invention.

[0029] It should be noted that these figures are diagrammatic and not drawn to scale. DETAILED DESCRIPTION

[0030] Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings.The described embodiments should not be construed as being limited to the description given in this section; the embodiments may have different forms.

[0031] The inventors have recognized that it may be advantageous to derive an acquisition threshold based on the size of the search space and the interval. Thus, for each search space, an acquisition threshold is calculated based on, for example, the number of search intervals, the integration time, and the measured noise value. This avoids the need to store and access a large data table each time an acquisition threshold is to be set.

[0032] There are currently four fully operational GNSS: the United States' Global Positioning System (GPS), Russia's Global Navigation Satellite System (GLONASS), China's BeiDou Navigation Satellite System (BDS), and the European Union's Galileo. GNSS receivers that can simultaneously acquire and track two or more GNSS are called multi-GNSS receivers.

[0033] The GNSS satellites of these various systems typically transmit GNSS signals in more than one frequency band. As an example, the frequency bands currently available under GPS include the L1, L2, and L5 frequency bands. For the L1 signal frequency band, the signal carrier frequency is typically in the range of 1.559 GHz to 1.610 GHz. For the L2 signal frequency band, the signal carrier frequency is typically in the range of 1.18845 GHz to 1.258 GHz. And, for the L5 signal frequency band, the signal carrier frequency is typically in the range of 1.164 GHz to 1.189 GHz. Additional or different frequency bands may become available for GPS in the future.

[0034] Different signal bands have different characteristics. As an example, L1, L2, and L5 within GPS have different chip rates: L1 has a chip rate of 1.023MHz, L2 has a chip rate of 511.5kHz, and L5 has a faster chip rate of 10.23MHz. Because L5 has a faster chip rate, the peak of the correlation function becomes narrower than the peaks of L1 and L2. For example, the correlation peak of L1 corresponds to 293m, while the correlation peak of L5 corresponds to 29.3m. Due to the narrower correlation function, it is easier to distinguish L5 signals transmitted by different paths (for example, due to reflections in a multipath environment) than to distinguish L1 or L2 signals transmitted by different paths. Therefore, the L5 signal is more resistant than the L1 signal in a multipath environment. As a further example of the chip rate GLO, the chip rate on L1 is 511kHz, and for L1, the BDS has 2.046MHz.

[0035] A GNSS receiver may operate in a single-band mode, where it performs signal processing to determine navigation measurements about signals in only one frequency band (e.g., only the L1 band or, as another example, only the L5 band). Alternatively, a GNSS receiver may operate in a dual-band or multi-band mode, where it performs signal processing using signals in multiple frequency bands within a particular constellation, such as the L1 and L5 dual-band mode in GPS. As another example, a GNSS receiver may be configured to operate in a multi-band mode utilizing three or more signal frequency bands (e.g., L1, L2, and L5). It is generally expected that multi-band processing will achieve more accurate navigation measurements than single-band processing.

[0036] Figure 11 shows a schematic block diagram of a GNSS receiver 100 for determining verification of a PVT solution in a global navigation satellite system according to an embodiment of the present invention. Figure 1 As shown, the GNSS receiver 100 is configured to receive GNSS satellite signals from GNSS satellites via an antenna 101. The received signals are passed from the antenna 101 to the RF front end 102, which performs tasks such as amplification, down-conversion, filtering, and digitization of the captured satellite signals. The RF front end 102 may include additional functions, such as frequency synthesis (not shown).

[0037] Receiver 100 is further configured to process received signals using processor 104 to extract observables and navigation data from each channel of baseband processing unit 103 and generate navigation solution 106. Processor 104 may include internal or external memory 105 for storing and / or retrieving data associated with the processing.

[0038] The navigation solution 106 generated by the receiver 100 may include the calculated position and velocity of the receiver 100 and the determination of the precise GNSS time. The navigation solution may be derived from any one or more of the GNSS band signals received at the antenna 101, which may include GNSS signals from different GNSS constellations. The navigation solution may also take into account the discounting of any one or more of the GNSS band signals received at the antenna 101. More specifically, the receiver 100 receives satellite signals from one or more GNSS constellations, and the processor 104 processes these signals to provide GNSS measurements, such as pseudoranges, carrier phases, pseudorange rates, etc., to the navigation filter. The processor 104 may, for example, implement a filter, such as a Kalman filter or a least-squares (LSQ) filter, for determining the navigation solution 106 based on the GNSS measurements.

[0039] The above system is used to determine a navigation solution. However, although the transmit frequency of the satellite is known, the Doppler shift as well as atmospheric effects mean that the frequency at the receiver may be different. The frequency may be higher or lower, and the receiver will therefore need to search a range of frequencies in order to find the frequency at the receiver.

[0040] The satellite signal includes a ranging code, and the delay from the code is also unknown. Therefore, a range of code delays must be searched to identify the signal and the correct code delay. Combined, there is a large range of frequencies and different code delays that must be searched. Once the signal is acquired, it can be tracked, but it must be acquired or found initially, which involves a relatively large search space.

[0041] GNSS signals are severely attenuated, so acquisition times of, for example, one second or more are required. A serial search over such a large search area would be unfeasibly slow, and so modern GNSS systems typically use parallel acquisition rather than serial acquisition.

[0042] Historically, short ranging codes have been used for signal acquisition, and longer ranging codes have been used for tracking. However, some newer signals (such as L1C, L2C L5, E1, E5, and E6) have only long ranging codes, typically with high bit rates. This results in a larger range of possible code delays, and therefore an increase in the size of the search space.

[0043] Typically, for signal acquisition, there is a matched filter bank for code phase search and a digital Fourier transformer for frequency search. Figure 2 A receiver structure for parallel acquisition and signal processing is shown. At 211, the received signal is multiplied with a locally generated replica signal f. This is performed at multiple different frequencies, each separated by Δf. At step 212, the received signal is also multiplied by the corresponding ranging code. Similar to frequency, different code delays are used, each separated by Δt. The signal is then coherently integrated 213, and the complex part is squared 214 and summed. Different frequencies and code delays define a two-dimensional search space, where each interval is separated by Δf in the frequency dimension and Δt in the time dimension. The value of each interval is stored in the corresponding interval.

[0044] There will be a value for each interval (each interval has a defined frequency and a defined code delay). Most intervals will simply have noise, but some intervals may have higher output values ​​than other intervals, which may indicate a signal at the frequency and code delay of the corresponding interval. A threshold must be set for the identification of the signal. If the threshold is set too low, there will be too many false positives. On the other hand, if the signal is set too high, the signal will not be identified. Therefore, it is desirable to infer the maximum noise level for a set of intervals.

[0045] Initially, according to I m , Q m ~N(0,mσ 2 ), the complex signal values ​​are normally distributed, where m is the coherent integration time in ms. When these values ​​are correlated with a random code, for a code length c, the values ​​are distributed as ~N(0, cmσ 2 ) or for a code of length 1023, the values ​​are distributed as ~N(0, 1023mσ 2 ). As is known, its amplitude follows the rule with a mean Rayleigh distribution Hence, after correlation with the random code, a Rayleigh distribution is formed. For L1CA, c is 1023, but for other code lengths it will be a different length.

[0046] For the Rayleigh distribution, the cumulative distribution function is:

[0047]

[0048] However, there are n intervals, so it is desirable to obtain the maximum n intervals, because accurately distinguishing the signal interval from the maximum noise interval will lead to the correct identification of the signal. The term noise interval refers to the search interval with noise. The cumulative distribution function of the maximum noise interval among all noise intervals is obtained by raising the cumulative distribution of F(x) to the power n.

[0049] For n different intervals X n Given by:

[0050]

[0051] With the following probability distribution function

[0052]

[0053] It can be seen that this has an exponentially decreasing tail. Extreme value theory proves that when n is large and the distribution has an exponentially decreasing tail, the distribution of the maximum noise interval converges towards a Gumbel distribution.

[0054]

[0055] in

[0056]

[0057] as well as

[0058]

[0059] From the original cumulative distribution function Calculate a n and b n .

[0060]

[0061] For the example integration time 1, this gives:

[0062]

[0063] The mean of the Gumbel function is given by:

[0064] μ Gumbel =b n+a n γ

[0065] where γ is the Euler-Mascheroni constant, which is approximately 0.5772. The variance of the Gumbel distribution is given by:

[0066]

[0067] The expected value of the maximum noise bin depends on n, the number of bins.

[0068] Knowing the expected value of the noise distribution and standard deviation allows more accurate setting of the signal detection threshold. The threshold can be set, for example, to Gumbel +σ Gumbel or μ Gumbel +2σ Gumbel or μ Gumbel +3σ Gumbel By setting the signal detection threshold to a predetermined number of standard deviations above the interval with expected maximum noise, false positives are minimized. Furthermore, if the signal detection threshold is consistently set to a predetermined number of standard deviations from the interval with expected maximum noise, there will be a consistent error rate regardless of the size of the search space.

[0069] Figure 3 The method according to the invention is shown. In a first step 301, the noise is determined in a plurality of search intervals. The noise level is preferably determined in all search intervals, but may alternatively be a subset of the search intervals. As described above, the average noise level per interval is given by Given, where m is the number of coherent integrations.

[0070] In step 302, the integration time t is determined. In the following step 303, the number of search intervals n is determined. Then, in step 304, the standard deviation σ of the individual search intervals is determined.

[0071] Then, the expected noise mean and expected standard deviation for the search interval with the maximum noise are calculated at step 305. This is based on the number of search intervals and the standard deviation of the noise for a single search interval. As described above, the expected noise mean for the maximum noise interval is given by:

[0072] μ Gumbel =b n +a n γ

[0073] And the expected variance is given by:

[0074]

[0075] in

[0076]

[0077] and

[0078]

[0079] in

[0080]

[0081] Then, the signal detection threshold is calculated in step 306. For a signal with a code length of 1023c, it will be 1023. In this example, the signal detection threshold is set to μ Gumbel +G Gumbel Here, the signal detection threshold is set to:

[0082]

[0083] Finally, at step 307 the signal detection threshold calculated in the previous step is set.

[0084] Once the signal detection threshold is set, you can use Figure 2 The system shown in , i.e., multiplying the replica carrier frequency at different frequencies and the replica pseudo-random code at different code delays. The signal in each interval can then be compared to the detection threshold. Once a signal above the signal detection threshold is found, the signal is identified. If a signal is identified, then there is no need to consider any remaining search intervals, since there is only one signal for each pseudo-random code. If a signal has been found, then the remaining intervals will not include the signal.

[0085] When a signal is identified, the code delay and frequency of the signal are determined to be the code delay and frequency of the corresponding interval from which the signal was identified.

[0086] Once the signal is identified, pseudoranges can be calculated.Once pseudoranges to multiple different satellites have been calculated, a position (or position, velocity and time) determination can be calculated using the pseudoranges to multiple satellites.

[0087] The above method can use a very large search area, that is, search over a large frequency range or a large code delay range. Although the frequency and code delay have been identified, they are only within Δf and Δt. Therefore, a second smaller search area can be used subsequently. For example, there can be a smaller search area, but each interval has a much smaller Δf and / or Δt.

[0088] Figure 5 A further method according to the invention is shown. Figure 5 The method from Figure 3The method continues. After the signal detection threshold is set in step 307, a signal above the signal threshold is identified in step 500. The signal has a frequency and a code delay. Then, a second search area is identified by setting 500a a second number of frequency intervals and setting 500b a second number of code delay intervals. The second search area can be much smaller and centered on the frequency and code delay initially identified. In fact, the entire search area can be within the search interval initially identified. Therefore, the frequency range Δf and the code delay range Δt of each search interval can be much smaller. Therefore, the result will give better frequency and code delay accuracy.

[0089] The noise is determined at step 501. The integration time is then determined at step 502, and the number of bins n is determined at step 503. Although the average noise per bin is consistent with the earlier method, there may be a different number of bins, so the expected maximum noise level may change. At step 504, the standard deviation of a single noise bin in the plurality of noise bins is determined.

[0090] Knowing the integration time t and the number of bins n, the expected noise level and standard deviation for the maximum noise bin is calculated at step 505. Next, a second signal detection threshold is calculated at step 506, and this may be different from the initial signal detection threshold. To maintain a constant error or false alarm rate, the number of standard deviations is the same as the mean from the previous step 306. For example, if step 306 is set to μ Gumbel +σ Gumbel , then the second signal detection threshold is set to μ Gumbel +σ Gumbel (Use μ Gumbel Finally, in step 507, a second signal detection threshold is set.

[0091] Using the above steps, the signal can then be acquired in a smaller search area to obtain a more accurate estimate of the frequency and code delay.

[0092] Although the smaller search area described Figure 5 , but it can also be used with larger search areas. However, for each search area there will be a constant error or false alarm rate because the signal detection threshold is set to the same number of standard deviations as the expected noise level of the maximum noise interval.

[0093] Figure 4 A method for obtaining the noise level for each interval is shown in FIG. In a first step 401, a signal is detected. In step 402, the signal is then correlated with a series of 1s. Although the example given here is a series of 1s, any random (but not specified pseudo-random) code can be used. Then, in step 403, the amplitude of the correlated signal is obtained.

[0094] It should be understood that the scope of the present disclosure is not limited to the above examples. Based on the above description, many variations will be apparent to those skilled in the art.

[0095] In the claims, any reference numerals placed between brackets shall not be interpreted as limiting the claims. The word "comprising" does not exclude the presence of elements or steps other than those listed in the claims. However, where the word "comprising" is used, this also discloses the possibility that the elements or steps listed as special cases are exhaustive, i.e., the device or method may consist of only those elements or steps. The word "one" or "one" before an element does not exclude the presence of multiple such elements. The embodiment may be implemented by hardware comprising several different elements. In a device claim that lists several devices, several of these devices may be specifically implemented by the same hardware item. The mere fact that certain measures are recorded in mutually different dependent claims does not indicate that the combination of these measures cannot be used advantageously. In addition, in the appended claims, a list comprising "at least one of A, B and C" should be interpreted as (A and / or B) and / or C.

[0096] In flowcharts, summaries, claims, and specifications relating to methods, the order in which the steps are listed is generally not intended to limit the order in which they are performed. The steps may be performed in an order different from that indicated (except where specifically indicated, or where subsequent steps depend on the results of previous steps). However, the order in which the steps are described may in some cases reflect a preferred order of operation.

[0097] In addition, in general, various embodiments may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be performed by a controller, microprocessor, or other computing device, although these are not limiting examples. Although various aspects described herein may be illustrated and described as block diagrams, flow charts, or using some other graphical representation, it is well understood that, as non-limiting examples, these blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0098] The embodiments described herein may be implemented by computer software executable by a data processor of the device (e.g., in a processor entity) or by hardware or by a combination of software and hardware. In addition, in this regard, it should be noted that any box of the logic flow as in the accompanying drawings may represent program steps, or interconnected logic circuits, boxes and functions, or a combination of program steps and logic circuits, boxes and functions. The software may be stored on physical media such as memory chips or memory blocks implemented within a processor, magnetic media such as hard disks or floppy disks, and optical media such as DVDs and their data variants CDs.

[0099] The memory may be of any type suitable for the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and removable memory. As non-limiting examples, the data processor may be of any type suitable for the local technical environment and may include one or more of a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a gate-level circuit, and a processor based on a multi-core processor architecture.

[0100] The embodiments discussed herein can be practiced in various components such as integrated circuit modules. The design of integrated circuits is typically a highly automated process. Complex and powerful software tools are available to convert logic level designs into semiconductor circuit designs that are ready to be etched and formed on semiconductor substrates.

Claims

1. A signal acquisition method in a navigation satellite system, the signal acquisition method setting a signal detection threshold for detecting a signal over a frequency range and a code delay range, the frequency range and the code delay range being divided into search intervals, each search interval having a frequency and a code delay, the method comprising: determining noise in a plurality of search intervals; determining a standard deviation of noise for a single search interval of the plurality of search intervals; Determine the integration time t; Determine the number n of search intervals; Calculating an expected noise and an expected standard deviation of the noise of the search interval having the maximum noise based on the number of the search intervals and the standard deviation of the noise of a single search interval; calculating the signal detection threshold based on a plurality of standard deviations from expected noise for the search interval having maximum noise; and The signal detection threshold is set.

2. The method according to claim 1, further comprising: detecting a signal level in each search interval; as well as One or more signals above the signal detection threshold are identified.

3. The method according to claim 2, further comprising: determining the frequency of the identified signal; as well as A code delay of the identified signal is determined.

4. The method according to claim 3, further comprising: A pseudorange to the satellite transmitting the signal is determined.

5. The method according to claim 1, wherein: Determining the noise includes correlating the signal with a predetermined code.

6. The method according to claim 5, wherein: The code includes all ones or all zeros.

7. The method according to claim 1, wherein: The average noise per search interval is The integration time t=m, and the expected noise of the search interval with maximum noise is given by μ Gumbel =b n +a n ·γ is given by, where γ is the Euler–Mascheroni constant, and and And the variance of the maximum noise is 8. The method according to any one of claims 3 to 7, further comprising: Setting a second signal detection threshold at a second frequency range different from the first frequency range and a second code delay range different from the first code delay range, the method further comprising: Setting a second number of frequency intervals; Setting a second number of code delay intervals; determining noise in the plurality of search intervals; determining the standard deviation of noise for a single search interval of the plurality of search intervals; Determine the integration time t; Determining the number n of the search intervals; Calculating an expected noise and an expected standard deviation of the search interval with maximum noise based on the number of search intervals and the standard deviation of noise of a single search interval; calculating the second signal detection threshold based on a plurality of standard deviations from expected noise for the search interval having maximum noise; and The second signal detection threshold is set.

9. The method according to claim 8, wherein: The second frequency range is a smaller frequency range and includes the frequency of the signal.

10. The method according to claim 8, wherein: The second code delay range is a smaller code delay range and includes the code delay of the signal.

11. The method according to claim 8, further comprising: detecting a signal level in each search interval; as well as One or more signals above the signal detection threshold are identified.

12. The method according to claim 11, further comprising: determining the frequency of the identified signal; as well as A code delay of the identified signal is determined.

13. A computer program, comprising computer program code, wherein the computer program code is configured to cause one or more physical computing devices to perform all the steps of the method according to any one of claims 1 to 12 when the computer program is run on the one or more physical computing devices.

14. A Global Navigation Satellite System (GNSS) receiver (100), the GNSS receiver being configured to set a signal detection threshold for detecting a signal, the GNSS receiver comprising a processor configured to execute the method according to any one of claims 1 to 12.

Images