First path detection method and system based on UWB CIR

Abstract

The invention belongs to the technical field of communication, and discloses a first path detection method and system based on UWB CIR. The method comprises the following steps: accumulating cross-correlation results output by each symbol to obtain a channel impulse response sequence; obtaining a phase sequence and an absolute value sequence of the channel impact response; performing window sliding at a certain window length to extract data of a phase sequence and an absolute value sequence; for the phase sequence, calculating the maximum phase deviation according to the data in the window; for the absolute value sequence, calculating a maximum value, a minimum value, a mean value and a ratio of the first two data in the window; and determining whether the current window has a first path. According to the method, threshold calculation does not need to be carried out firstly, first path detection is directly carried out, and the range of first path detection is increased; in the detection process, complex calculation does not exist, and engineering implementation is facilitated; and the phase and amplitude change characteristics of the first path channel impact response are utilized, so that the method has higher detection success rate and detection robustness.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and particularly relates to a first path detection method and system based on UWB CIR. Background Art

[0002] The outdoor positioning technology based on GNSS is relatively mature. However, indoors, since satellite signals are easily blocked and normal positioning services cannot be completed, and the positioning accuracy cannot meet the service requirements. In recent years, people's demand for high-precision positioning services has become increasingly strong. According to statistics, 70%-80% of people's activities occur indoors. Therefore, developing indoor positioning technology is of great significance. Based on various different requirements, many corresponding positioning technologies have emerged and achieved good results, such as infrared, radio frequency identification, ultrasonic, WIFI, Bluetooth, Zigbee, visual positioning and other technologies. However, they all have their own drawbacks, either with low positioning accuracy or demanding harsh environments, and cannot meet people's requirements for high accuracy and good environmental adaptability of the indoor positioning perception system.

[0003] Many advantages of the UWB positioning technology enable this technology to achieve high-precision indoor positioning. Compared with other wireless positioning technologies, UWB has many advantages such as strong anti-interference ability, extremely wide bandwidth, fast transmission rate, and low power consumption. In the positioning process using ranging results, the direct path (first path) is particularly important. The robustness of the first path detection performance will directly affect the accuracy of the positioning result. A simple and reliable first path detection algorithm is one of the current research focuses.

[0004] Through the above analysis, the problems and defects existing in the prior art are as follows: In the prior art, during the first path detection in indoor positioning, the calculation is complex, which is not conducive to engineering implementation; moreover, the detection success rate and the robustness of the detection are poor. Summary of the Invention

[0005] To overcome the problems existing in the related technologies, the disclosed embodiments of the present invention provide a first path detection method and system based on UWB CIR, which particularly relates to ultra-wideband (UWB) communication positioning technology.

[0006] The technical solution is as follows: The first path detection method based on UWB CIR includes:

[0007] S1, accumulating the cross-correlation results output for each symbol to obtain a channel impulse response sequence;

[0008] S2, respectively calculating the phase and absolute value of the channel impulse response sequence to obtain the phase sequence and absolute value sequence of the channel impulse response;

[0009] S3. Slide a window with a certain window length to extract data from the phase sequence and the absolute value sequence;

[0010] S4. For the phase sequence, calculate the maximum phase deviation based on the data within the window;

[0011] S5. For the absolute value sequence, calculate the maximum value, minimum value, mean value within the window, and the ratio of the first two data;

[0012] S6. Compare the calculated results with relevant thresholds to determine whether there is a first path in the current window;

[0013] S7. If there is no first path, update the maximum noise value and return to step S3 to continue extracting data from the next window for calculation;

[0014] S8. If there is a first path, end the algorithm, output that the first path detection is successful, and output the relevant information of the first path;

[0015] S9. If no first path is detected until the end of the sequence, also end the algorithm and output that the first path detection fails.

[0016] In step S1, the calculation formula for obtaining the channel impulse response sequence is:

[0017]

[0018] Where C(i) is the i-th data in the channel impulse response sequence, and C(i) is a complex number; N symb represents the total number of symbols, and A k (i) is the cross-correlation result of the i-th data in the k-th symbol.

[0019] In step S2, calculate the phase and absolute value of the channel impulse response sequence respectively to obtain the phase sequence and absolute value sequence of the channel impulse response. The expressions are:

[0020] p′(i) = angle(C(i))

[0021] Where p'(i) is the phase value calculated based on the channel impulse response, angle is the angle value, i is the index value of C(i) in the channel impulse response sequence, and the range is 1 to N CIR , N CIR is the total number of data included in the channel response sequence;

[0022] When i = 1, p(i) = p'(i).

[0023] When i > 1, judge the result of (p'(i) - p(i - 1)). If (p'(i) - p(i - 1)) > 180°, then p(i) = p'(i) - 360°. If (p'(i) - p(i - 1)) < -180°, then p(i) = p'(i) + 360°. In other cases, p(i) = p'(i);

[0024] where p(i) is the phase value of the i-th phase in the phase sequence.

[0025] Furthermore, the method for calculating the absolute value sequence according to the channel impulse response sequence is as follows:

[0026] S(i) = abs(C(i

[0027] In the formula, S(i) is the i-th absolute value amplitude in the absolute value sequence, and abs(x) is the operation of taking the absolute value of x;

[0028] In step S3, a certain window length is N w = 3, and the phase sequence and the absolute value sequence use their respective sliding windows;

[0029] The index value of the first data in the sliding window represents the index of the current window;

[0030] Each time the sliding window slides, the data with the lowest index will be discarded, and a data with a higher index will be added.

[0031] In step S4, the method for calculating the maximum phase deviation is as follows:

[0032] Δp max (i) = max([p(i), …, p(i + N w - 1)]) - min([p(i), …, p(i + N w - 1)])

[0033] In the formula, Δp max (i) is the maximum phase deviation, max(x) is to find the maximum value in the x sequence, min(x) is to find the minimum value in the x sequence, and N w is the window length of the sliding window.

[0034] Furthermore, the method for calculating the maximum value in the current window is as follows:

[0035] S max (i) = max([S(i), …, S(i + N w - 1)])

[0036] In the formula, S max (i) is the maximum value in the current sliding window;

[0037] The calculation method of the minimum value within the current window is as follows:

[0038] S min (i) = min([S(i), …, S(i + N w -1)])

[0039] In the formula, S min (i) is the minimum value within the current sliding window;

[0040] The calculation method of the average value within the current window is as follows:

[0041]

[0042] Among them, S avg (i) is the average value within the current sliding window, and τ is a variable traversing from i to i + N w -1.

[0043] In step S5, the calculation method of the ratio of the first two data within the sliding window is as follows:

[0044] R(i) = S(i) / max(S(i + 1), d min )

[0045] In the formula, R(i) is the ratio of the first two data within the sliding window, S(i) is the absolute value corresponding to C(i), S(i) = abs(C(i)), and abs(x) is the operation of taking the absolute value of x; d min is the minimum value that may occur except 0 for S(i); when S(i + 1) < d min , the dividend will be replaced by d min .

[0046] In step S6, in the method of determining whether there is a leading diameter in the current window, if the following conditions are simultaneously met, it indicates that there is a leading diameter in the current window:

[0047] The maximum phase deviation is less than the set threshold: Δp max (i) < Δp th ;

[0048] The maximum value is less than the average value multiplied by the set proportionality coefficient: S max (i) < R s *S avg (i);

[0049] The minimum value is greater than the maximum value of the noise: S min (i) > S noi_max ;

[0050] The ratio of the first two data within the window satisfies a certain relationship: R(i) < R th ;

[0051] where Δp th is the maximum phase difference threshold, R s is the ratio coefficient threshold of the maximum value to the average value within the sliding window, S noi_max is the maximum value of the noise segment, with an initial value of 0 and updated in step S7, R th is the ratio threshold of the first two data within the window.

[0052] In step S7, the method for updating the maximum noise value is as follows: when there is no first path detected in the current window, use the maximum value S max (i) of the current window to compare with the currently stored maximum noise value S noi_max . When S max (i) > S noi_max , S noi_max = S max (i). Otherwise, S noi_max remains unchanged; the initial value of the maximum noise value S noi_max is 0;

[0053] In step S8, the output first path information includes: the current window index i is the index value of the first path front edge point, the absolute value sequence within the current window is the amplitude information of the first path, and the phase sequence within the current window is the phase information of the first path.

[0054] In step S9, it outputs that the first path detection fails, including: when the counting index i does not satisfy i ≤ (N CIR - N w ), the sequence ends and no first path is detected yet, then it outputs that the first path detection fails.

[0055] Another object of the present invention is to provide a first path detection system based on UWB CIR, which implements the first path detection method based on UWB CIR. This system includes:

[0056] A channel impulse response sequence obtaining module, which is used to accumulate the cross - correlation results output for each symbol to obtain the channel impulse response sequence;

[0057] A phase sequence and absolute value sequence obtaining module, which is used to calculate the phase and absolute value of the channel impulse response sequence respectively to obtain the phase sequence and absolute value sequence of the channel impulse response;

[0058] A phase sequence and absolute value sequence data extraction module, which slides the window with a certain window length to extract the data of the phase sequence and absolute value sequence;

[0059] A maximum phase deviation calculation module, which calculates the maximum phase deviation according to the data within the window for the phase sequence;

[0060] The ratio calculation module is used to calculate the maximum value, minimum value, average value within the window, and the ratio of the first two data for the absolute value sequence;

[0061] The current window start diameter judgment module uses the calculated results to compare with relevant thresholds to determine whether there is a start diameter in the current window;

[0062] The updated noise maximum value module, if there is no start diameter, updates the noise maximum value and returns to step S3 to continue extracting data of the next window for calculation;

[0063] The start diameter related information output module, if there is a start diameter, the algorithm ends, outputs that the start diameter detection is successful, and outputs the start diameter related information;

[0064] The start diameter detection failure output module, if no start diameter is detected until the end of the sequence, the algorithm also ends and outputs that the start diameter detection fails.

[0065] Combining all the above technical solutions, the beneficial effects of the present invention are as follows: The present invention does not need to calculate the threshold using the channel impulse response sequence (CIR, channel impulse response), and can directly perform the start diameter detection; during the detection process, there is no complex calculation, which is beneficial to engineering implementation; at the same time, it utilizes the phase and amplitude change characteristics of the start diameter channel impulse response, and has a higher detection success rate and detection robustness. Description of the Drawings

[0066] The drawings here are incorporated into the specification and constitute a part of this specification, showing the embodiments that conform to the present disclosure, and are used together with the specification to explain the principles of the present disclosure;

[0067] Figure 1 is the flowchart of the start diameter detection method based on UWB CIR provided by the embodiment of the present invention;

[0068] Figure 2 is the schematic diagram of the window extraction data principle of the start diameter detection method based on UWB CIR of the present invention;

[0069] Figure 3 is the schematic diagram of the sliding window sliding principle of the start diameter detection method based on UWB CIR of the present invention;

[0070] Figure 4 is the schematic diagram of the start diameter detection system based on UWB CIR provided by the embodiment of the present invention;

[0071] In the figure: 1. Channel impulse response sequence obtaining module; 2. Phase sequence and absolute value sequence obtaining module; 3. Phase sequence and absolute value sequence data extraction module; 4. Maximum phase deviation calculation module; 5. Ratio calculation module; 6. Current window first path determination module; 7. Update noise maximum value module; 8. First path related information output module; 9. First path detection failure output module. Detailed implementation manners

[0072] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the detailed implementation manners of the present invention with reference to the accompanying drawings. Many specific details are set forth in the following description to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific implementations disclosed below.

[0073] The present invention directly performs first path detection without using the CIR calculation threshold, increasing the range of first path detection; during the detection process, there is no complex calculation, which is beneficial to engineering implementation; at the same time, it utilizes the phase and amplitude change characteristics of the first path channel impulse response, having a higher detection success rate and detection robustness.

[0074] Embodiment 1, as Figure 1 shown, the first path detection method based on UWB CIR provided by the embodiment of the present invention includes the following steps:

[0075] S1. Accumulate the cross-correlation results output for each symbol to obtain the channel impulse response sequence;

[0076] S2. Calculate the phase and absolute value of the channel impulse response sequence respectively to obtain the phase sequence and absolute value sequence of the channel impulse response;

[0077] S3. Slide a window with a certain window length to extract the data of the phase sequence and absolute value sequence;

[0078] S4. For the phase sequence, calculate the maximum phase deviation according to the data within the window;

[0079] S5. For the absolute value sequence, calculate the maximum value, minimum value, average value within the window, and the ratio of the first two data;

[0080] S6. Compare the calculated results with relevant thresholds to determine whether there is a first path in the current window;

[0081] S7. If there is no first path, update the noise maximum value and return to step S3 to continue extracting data of the next window for calculation;

[0082] S8, if there is a leading diameter, the algorithm ends, outputs that the leading diameter detection is successful, and outputs the relevant information of the leading diameter;

[0083] S9, if no leading diameter is detected until the end of the sequence, the algorithm also ends, and outputs that the leading diameter detection fails.

[0084] Exemplarily, in step S1, the calculation formula for obtaining the channel impulse response sequence is:

[0085]

[0086] where, A k (i) is the cross - correlation result of the i - th data in the k - th symbol. N symb represents the total number of symbols. In step S2, the method for calculating the phase sequence according to the channel impulse response sequence is as follows:

[0087] p′(i) = angle(C(i))

[0088] where, p'(i) is the phase value calculated according to the channel impulse response, C(i) is the i - th data in the channel impulse response sequence, and C(i) is a complex number. i is the index value of C(i) in the channel impulse response sequence, with a range of 1 to N CIR , N CIR is the total number of data included in the channel response sequence.

[0089] When i = 1, p(i) = p'(i).

[0090] When i > 1, judge the result of (p'(i) - p(i - 1)). If (p'(i) - p(i - 1)) > 180°, then p(i) = p'(i) - 360°. If (p'(i) - p(i - 1)) < - 180°, then p(i) = p'(i) + 360°. In other cases, p(i) = p'(i);

[0091] where, p(i) is the phase value of the i - th phase in the phase sequence.

[0092] The method for calculating the absolute - value sequence according to the channel impulse response sequence is as follows:

[0093] S(i = abs(C(i));

[0094] where, S(i) is the absolute - value amplitude of the i - th in the absolute - value sequence, and abs(x) is the operation of taking the absolute value of x.

[0095] Exemplarily, in step S3, the set window length is N w = 3, that is, the sliding window contains 3 data. And the phase sequence and the absolute - value sequence use their respective sliding windows.

[0096] Taking the sliding window of the phase sequence as an example, the method of extracting data each time is as Figure 2 shown.

[0097] As Figure 3 shown, the index value of the first data in the sliding window also represents the index of the current window. For example, the data in the initial window is [p(1) p(2) p(3)], and the index of the current window is 1.

[0098] Each time the sliding window slides, the data with the lowest index will be discarded, and a data with a higher index will be added. For example, after the first slide of the window, p(1) is discarded and p(4) is added to the window, and 3 data are maintained in the window.

[0099] In step S4, the calculation method of the maximum phase deviation is as follows:

[0100] Δp max (i) = max([p(i), …, p(i + N w - 1)]) - min([p(i), …, p(i + N w - 1)])

[0101] where max(x) is to find the maximum value in the x sequence, min(x) is to find the minimum value in the x sequence, and N w is the window length of the sliding window.

[0102] In step S5, for the absolute value sequence, calculate the maximum value, minimum value, average value in the window, and the ratio of the first two data. The calculation method of the maximum value in the current window is as follows:

[0103] S max (i) = max(S(i), …, S(i + N w - 1)])

[0104] where S max (i) is the maximum value in the current sliding window.

[0105] The calculation method of the minimum value in the current window is as follows:

[0106] S min (i) = min([S(i), …, S(i + N w - 1)]);

[0107] where S min (i) is the minimum value in the current sliding window.

[0108] The calculation method of the average value in the current window is as follows:

[0109]

[0110] Among them, S avg (i) is the average value within the current sliding window, and τ is a variable traversing from i to i + N w -1. The calculation method of the ratio of the first two data within the sliding window is as follows:

[0111] R(i) = S(i) / max(S(i + 1), d min )

[0112] Among them, R(i) is the ratio of the first two data within the sliding window, S(i) is the absolute value corresponding to C(i), S(i) = abs(C(i)), and abs(x) is the operation of taking the absolute value of x. d min is the minimum value that S(i) may take except 0. When S(i + 1) < d min , the dividend will be replaced by d min .

[0113] In step S6, the method for determining whether there is a leading diameter in the current window is as follows:

[0114] Satisfying the following several conditions simultaneously indicates that there is a leading diameter in the current window:

[0115] The maximum phase deviation is less than the set threshold: Δp max (i) < Δp th ;

[0116] The maximum value is less than the average value multiplied by the set proportionality coefficient: S max (i) < R s *S avg (i);

[0117] The minimum value is greater than the maximum value of the noise: S min (i) > S noi_max ;

[0118] The ratio of the first two data within the window satisfies a certain relationship: R(i) < R th .

[0119] Among them, Δp th is the maximum phase difference threshold, R s is the threshold of the ratio of the maximum value to the average value within the sliding window, S noi_max is the maximum value of the noise segment, with an initial value of 0, which is updated in step S7, and R th is the threshold of the ratio of the first two data within the window.

[0120] In step S7, the method for updating the maximum value of the noise is as follows:

[0121] When it is detected that there is no leading diameter in the current window, use the maximum value S max(i) Compare with the currently stored maximum noise value S noi_max When S max (i) > S noi_max then S noi_max = S max (i). Otherwise, S noi_max remains unchanged.

[0122] The initial value of the maximum noise value S noi_max is 0.

[0123] Exemplarily, in step S8, when the four conditions of step S7 are simultaneously satisfied, it indicates that there is a leading path in the current window, the leading path detection is successful, and the leading path information is output.

[0124] The output leading path information includes: the current window index i is the index value of the leading path front point, the absolute value sequence within the current window is the amplitude information of the leading path, and the phase sequence within the current window is the phase information of the leading path.

[0125] Exemplarily, in step S9, when the counting index i does not satisfy i ≤ (N CIR - N w ), it indicates that the sequence has ended and the leading path has still not been detected, and the leading path detection fails is output.

[0126] Embodiment 2, as Figure 4 shown, the leading path detection system based on UWB CIR provided by the embodiment of the present invention includes the following steps:

[0127] Channel impulse response sequence obtaining module 1, for accumulating the cross-correlation results output for each symbol to obtain the channel impulse response sequence;

[0128] Phase sequence and absolute value sequence obtaining module 2, for respectively calculating the phase and absolute value of the channel impulse response sequence to obtain the phase sequence and absolute value sequence of the channel impulse response;

[0129] Phase sequence and absolute value sequence data extraction module 3, for sliding window extraction of the data of the phase sequence and absolute value sequence with a certain window length;

[0130] Maximum phase deviation calculation module 4, for calculating the maximum phase deviation according to the data within the window for the phase sequence;

[0131] Ratio calculation module 5, for calculating the maximum value, minimum value, mean value within the window, and the ratio of the first two data for the absolute value sequence;

[0132] Current window leading path determination module 6, for comparing the calculated results with relevant thresholds to determine whether there is a leading path in the current window;

[0133] The updated noise maximum value module 7 is used to update the noise maximum value if there is no first path, continue to extract the data of the next window for calculation;

[0134] The first path related information output module 8 is used to end the algorithm if there is a first path, output that the first path detection is successful, and output the first path related information;

[0135] The first path detection failure output module 9 is used to end the algorithm if no first path is detected until the end of the sequence, and output that the first path detection fails.

[0136] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0137] As described above, only the relatively preferred specific implementation manners of the present invention are provided, 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 first path detection method based on UWB CIR, characterized in that: The method includes: S1, accumulate the cross-correlation results of each symbol output to obtain the channel impulse response sequence; S2, respectively calculate the phase and absolute value of the channel impulse response sequence to obtain the phase sequence and absolute value sequence of the channel impulse response; S3, sliding the window with a certain window length to extract the data of the phase sequence and the absolute value sequence; S4, for the phase sequence, the maximum phase deviation is calculated based on the data in the window; S5, for the absolute value sequence, calculate the maximum value, minimum value, mean value, and the ratio of the previous two data in the window; S6, comparing the calculated result with the relevant threshold value to determine whether there is a first path in the current window; S7, if there is no first path, update the maximum noise value, and return to step S3 to continue extracting the data of the next window for calculation; S8, if the first path exists, the algorithm ends, outputs the first path detection success, and outputs the first path related information; S9: If the first path is not detected by the end of the sequence, the algorithm ends and the first path detection fails.

2. The first path detection method based on UWB CIR according to claim 1, characterized in that: In step S1, the calculation formula for obtaining the channel impulse response sequence is: Where C(i) is the i-th data in the channel impulse response sequence, C(i) is a complex number; N symb Indicates the total number of symbols, A k (i) is the cross-correlation result of the i-th data in the k-th symbol.

3. The first path detection method based on UWB CIR according to claim 2 is characterized in that: In step S2, the phase and absolute value of the channel impulse response sequence are calculated respectively to obtain the phase sequence and absolute value sequence of the channel impulse response, which are expressed as follows: p'(i)=angle(C(i)) Where p'(i) is the phase value calculated based on the channel impulse response, angle is the angle value, and i is the index value of C(i) in the channel impulse response sequence, ranging from 1 to N. CIR , N CIR is the total number of data contained in the channel response sequence; When i=1, p(i)=p'(i); When i>1, determine the result of (p'(i)-p(i-1)). If (p'(i)-p(i-1))>180°, then p(i)=p'(i)-360°. If (p'(i)-p(i-1))<-180°, then p(i)=p'(i)+360°. In other cases, p(i)=p'(i). Where p(i) is the phase value of the i-th phase in the phase sequence.

4. The first path detection method based on UWB CIR according to claim 3 is characterized in that: The method for calculating the absolute value sequence based on the channel impulse response sequence is as follows: S(i)=abs(C(i)) Where S(i) is the absolute value amplitude of the i-th absolute value sequence, and abs(x) is the absolute value operation of x; In step S3, a certain window length is N w =3, and the phase sequence and the absolute value sequence use their own sliding windows respectively; The index value of the first data in the sliding window represents the index of the current window; Each time the sliding window slides, the data with the lowest index will be discarded and the data with a higher index will be added.

5. The first path detection method based on UWB CIR according to claim 4 is characterized in that: In step S4, the maximum phase deviation is calculated as follows: Δp max (i)=max([p(i),…,p(i+N w -1)])-min([p(i)),…,p(i+N w -1)]) In the formula, Δp max (i) is the maximum phase deviation, max(x) is the maximum value in the x sequence, min(x) is the minimum value in the x sequence, N w is the window length of the sliding window.

6. The first path detection method based on UWB CIR according to claim 5, characterized in that: The maximum value in the current window is calculated as follows: S max (i)=max([S(i),…,S(i+N w -1)]) In the formula, S max (i) is the maximum value in the current sliding window; The calculation method for the minimum value in the current window is as follows: S min (i)=min([S(i),…,S(i+N w -1)]) In the formula, S min (i) is the minimum value in the current sliding window; The average value in the current window is calculated as follows: Among them, S avg (i) is the average value in the current sliding window, and τ is the average value of the traversal from i to i+N. w -1 variable.

7. The first path detection method based on UWB CIR according to claim 1, characterized in that: In step S5, the ratio of the first two data in the sliding window is calculated as follows: R(i)=S(i) / max(S(i+1),d min ) Where R(i) is the ratio of the first two data in the sliding window, S(i) is the absolute value corresponding to C(i), S(i) = abs(C(i)), abs(x) is the absolute value operation of x; d min S(i) is the smallest possible value other than 0; when S(i+1) <d min When the dividend is d min replace.

8. The first path detection method based on UWB CIR according to claim 1, characterized in that: In step S6, in the method of determining whether the current window has a first path, if the following conditions are met at the same time, it means that the current window has a first path: The maximum phase deviation is less than the set threshold: Δp max (i)<Δp th ; The maximum value is less than the average value multiplied by the set proportionality factor: S max (i) <R s *S avg (i); The minimum value is greater than the maximum value of the noise: S min (i)>S noi_max ; The ratio of the first two data in the window satisfies a certain relationship: R(i) <R th ; In the formula, Δp th is the maximum phase difference threshold, R s is the ratio coefficient threshold of the maximum value to the average value in the sliding window, S noi_max is the maximum value of the noise segment, the initial value is 0, and it is updated in step S7. th is the ratio threshold of the first two data in the window.

9. The first path detection method based on UWB CIR according to claim 1, characterized in that: In step S7, the method for updating the maximum noise value is: when the current window is detected and there is no first path, the maximum value S of the current window is used. max (i) and the currently stored maximum noise value S noi_max For comparison, when S max (i)>S noi_max When S noi_max =S max (i); otherwise, S noi_max Remain unchanged; the maximum noise value S noi_max The initial value of is 0; In step S8, the output first path information includes: the current window index i is the index value of the leading point of the first path, the absolute value sequence in the current window is the amplitude information of the first path, and the phase sequence in the current window is the phase information of the first path; In step S9, outputting the first path detection failure includes: when the counting index i does not satisfy i≤(N CIR -N w ), the sequence ends, the first path is still not detected, and the output first path detection fails.

10. A first path detection system based on UWB CIR, characterized in that: The system implements the first path detection method based on UWB CIR as described in any one of claims 1 to 9, and the system includes: A channel impulse response sequence obtaining module (1) is used to accumulate the cross-correlation results of each symbol output to obtain a channel impulse response sequence; A phase sequence and absolute value sequence acquisition module (2) is used to respectively calculate the phase and absolute value of the channel impulse response sequence to obtain the phase sequence and absolute value sequence of the channel impulse response; A phase sequence and absolute value sequence data extraction module (3) performs sliding window with a certain window length to extract the data of the phase sequence and the absolute value sequence; A maximum phase deviation calculation module (4), for a phase sequence, calculates the maximum phase deviation according to data in the window; A ratio calculation module (5), for calculating the maximum value, minimum value, mean value, and ratio of the first two data in the window for the absolute value sequence; The current window first path judgment module (6) compares the calculated result with the relevant threshold value to determine whether the current window has a first path; Update the noise maximum value module (7), if the first path does not exist, update the noise maximum value, return to step S3 to continue to extract the data of the next window for calculation; First path related information output module (8), if the first path exists, the algorithm ends, outputs the first path detection success, and outputs the first path related information; The first path detection failure output module (9) is used to output that the first path has not been detected by the end of the sequence. Similarly, the algorithm ends and the first path detection failure is output.

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