An underwater single-frequency signal direction finding method and system

Abstract

The present application relates to the field of target orientation measurement, and particularly relates to a method and system for underwater single-frequency signal direction finding. The method comprises the following steps: calculating a coarse time delay difference by using signal correlation; calculating a list of ambiguity numbers by using phase difference of different interval elements; and obtaining a high-precision time delay difference estimation by resolving the phase difference ambiguity according to the coarse time delay difference, so as to perform high-precision stable direction finding. The present application can realize high-precision direction finding of underwater single-frequency signals including black box signals.

Description

Technical Field

[0001] This invention relates to the field of target orientation determination, and specifically to an underwater single-frequency signal orientation determination method and system. Background Technology

[0002] In traditional linear array direction finding, large-spacing primitives directly estimate the time delay difference using two-channel correlation to achieve direction finding. This method has low direction finding accuracy. Direction finding by estimating the time delay difference using the phase difference of two channels has high accuracy, but the phase difference is ambiguous, requiring additional primitives to assist in de-ambiguity. The traditional approach is to add a primitive with a spacing less than half a wavelength, using this primitive to estimate the unambiguous phase difference. Based on the spacing relationship of the primitives, the ambiguity number of the phase difference between large-spacing primitives is estimated, and then direction finding is achieved. This method relies on the premise that the spacing between two primitives is less than half a wavelength. In practical applications, high-frequency signals have short wavelengths, resulting in very small spacing between unambiguous phase primitives, making it difficult to achieve in manufacturing processes.

[0003] Therefore, it is necessary to study a linear array unambiguous direction finding method with an element spacing greater than half a wavelength to solve the existing technical problems. Summary of the Invention

[0004] The purpose of this invention is to solve the current problem of high-precision direction finding using single-frequency underwater signals. This invention aims to provide an underwater single-frequency signal direction finding method to achieve its objective.

[0005] The above-mentioned technical objectives of the present invention will be achieved through the technical solutions described below.

[0006] This invention proposes an underwater single-frequency signal direction finding method, comprising:

[0007] Step 1) Correlate the received signal of the linear array with the local single-frequency signal;

[0008] Step 2) Using the relevant results obtained in Step 1), estimate the coarse time delay difference;

[0009] Step 3) Estimate the multi-channel phase difference of the received signal using a notch filter;

[0010] Step 4) Calculate the ambiguity number list based on the multi-channel phase difference;

[0011] Step 5) Use the coarse time delay difference obtained in Step 2) and the list of fuzzy numbers obtained in Step 4) to solve for the unfuzzy phase difference;

[0012] Step 6) Use the unambiguous phase difference obtained in step 5) to perform direction finding.

[0013] As an improvement to the above technical solution, the linear array includes a first element, a second element, and a third element, wherein the first element and the third element are spaced apart, and the first element and the second element are spaced apart; the signals received by the first element, the second element, and the third element are processed in the first channel, the second channel, and the third channel, respectively.

[0014] As an improvement to the above technical solution, the relevant results obtained in step 1) include the pulse compression results for each channel; wherein the pulse compression result y of the i-th channel i (n1) is represented as:

[0015]

[0016] Where, x i (n) represents the bandpass filtering result of the received signal in the i-th channel, s l (N-(mn)) represents the shift signal of the local single-frequency signal sl(n), where m represents the local single-frequency signal sl(n) relative to x. i (n) The number of points shifted, where N represents the local single-frequency signal s. l The length of (n), where n is the number of sampling points.

[0017] As one improvement to the above technical solution, the bandpass filtering result of the i-th channel received signal is expressed as follows:

[0018]

[0019] Among them, s i (n) represents the discrete received signal of the i-th channel, and the coefficient b m This represents the m-th filter coefficient, where M represents the order of the bandpass filter. An M-order filter has a total of M+1 coefficients.

[0020] s l (n)=exp{j·2πf c n·T s}

[0021] Where j is the imaginary sign, f c T is the center carrier frequency of the received signal. s is the sampling rate; exp{·} is the complex exponentiation operation.

[0022] As one improvement to the above technical solution, step 2) includes:

[0023] Step 2-1) Find the peak value of the pulse compression result segment by segment and compare it with the pre-set threshold to find the position of the received signal;

[0024] Step 2-2) Find the peak value of the pulse compression result, estimate the relative time delay between the received signal and the local signal, and calculate the coarse time delay difference.

[0025] As an improvement to the above technical solution, step 3) includes:

[0026] Based on the position of the received signal obtained in step 2-1), the received signal data segment is obtained, the phase of each channel is calculated using a notch filter, and then the phase difference between the first channel and the second channel, as well as the phase difference between the first channel and the third channel, are calculated.

[0027] As an improvement to the above technical solution, step 4) includes:

[0028] Step 4-1) Calculate the time delay difference range between the first and third channels based on the target azimuth range, and then calculate the ambiguity number range of the phase difference between the first and third channels; the upper limit n of the ambiguity number of the phase difference between the first and third channels. 13max The calculation formula is as follows:

[0029]

[0030] in, L represents the target's maximum azimuth angle. 13 The distance between the first and third primitives is represented by , c represents the speed of sound propagation in water, and floor() represents the floor function; the lower limit of the phase difference ambiguity number between the first and third channels is -n. 13max .

[0031] Step 4-2) Calculate the ambiguity number list of the phase difference between the first and second channels based on the ambiguity number range of the phase difference between the first and third channels; where the j-th ambiguity number n of the phase difference between the first and second channels is... 12,j Represented as:

[0032]

[0033] Where, p 13 p represents the phase difference between the principal values ​​of the first and third channels. 12 n represents the phase difference between the principal values ​​of the first and second channels. 13,j L represents the j-th ambiguity number representing the phase difference between the first and third channels. 12 The interval between the first and second primitives is represented by `round()`, which is the rounding function.

[0034] As an improvement to the above technical solution, step 5) includes:

[0035] Step 5-1) Calculate the coarse ambiguity number of the phase difference between the first and second channels based on the coarse time delay difference obtained in Step 2).

[0036]

[0037] in, This represents the coarse delay difference between the first and second channels.

[0038] Step 5-2) Based on the coarse fuzzy number of the phase difference between the first and second channels Searching for the accurate fuzzy number n from the list of fuzzy numbers obtained in step 4). 12,j Calculate the accurate blur number for the first and second channels:

[0039]

[0040] Wherein, C is the list of phase difference ambiguity numbers for the first and second channels obtained in step 4);

[0041] Step 5-3) Calculate the unambiguous phase difference based on the coarse ambiguity numbers of the first and second channels; the formula for the unambiguous phase difference is as follows:

[0042] P 12 =p 12 +n 12 2π

[0043] Among them, P 12 For the first and second channels to have no ambiguity phase difference, n 12 The ambiguity number is the phase difference between the first and second channels.

[0044] As one improvement to the above technical solution, step 6) includes:

[0045] Step 6-1) Calculate the high-precision time delay difference t between the first and second channels based on the unambiguous phase difference obtained in Step 5). 12 :

[0046]

[0047] Among them, t 12 This indicates the high-precision time delay difference between channels 1 and 2;

[0048] Step 6-2) Calculate the target's azimuth relative to the receiving linear array, phi, based on the high-precision time delay difference:

[0049]

[0050] In this context, a positive phi indicates that the direction is on the right, while a negative phi indicates that the direction is on the left.

[0051] An underwater single-frequency signal direction finding system of the present invention includes:

[0052] The signal correlation processing module is used to correlate the received signal of the linear array with the local single-frequency signal;

[0053] The coarse delay difference estimation module is used to estimate the coarse delay difference using the correlation results obtained from the signal correlation processing module.

[0054] The phase difference estimation module is used to estimate the multi-channel phase difference of the received signal using a notch filter.

[0055] The fuzzy number calculation module is used to calculate a list of fuzzy numbers based on the phase difference of multiple channels;

[0056] The unambiguous phase difference calculation module is used to solve for the unambiguous phase difference using the coarse time delay difference obtained from the coarse time delay difference estimation module and the fuzzy number list obtained from the fuzzy number calculation module; and

[0057] The direction finding module is used to perform direction finding using the unambiguous phase difference obtained by the unambiguous phase difference calculation module.

[0058] Beneficial technical effects of the present invention:

[0059] Compared with the prior art, the advantages of the present invention are as follows: the underwater single-frequency signal direction finding method of the present invention improves the direction finding accuracy by using phase difference to estimate the time delay difference; and improves the defuzzification accuracy by using small aperture primitives with fuzzy phase difference and large apertures with fuzzy phase difference and correlation peak time delay estimation to jointly defuzzify. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the method flow in an embodiment of the present invention;

[0061] Figure 2 This is a schematic diagram of the array element distribution in an embodiment of the present invention. Detailed Implementation

[0062] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0063] Example 1

[0064] like Figure 1 As shown, the underwater single-frequency signal direction finding method proposed in this invention achieves unambiguous phase difference estimation by jointly deambiguing the ambiguity of small aperture primitives and large apertures, as well as the correlation peak time delay estimation, thereby realizing target direction finding.

[0065] like Figure 2 The diagram shown is a schematic representation of the array element distribution in an embodiment of the present invention. The numbers 1, 2, and 3 in the diagram correspond to channels 1, 2, and 3 (the first, second, and third channels), respectively.

[0066] Specifically, the steps of this invention are as follows:

[0067] Step 1) Correlate the received signal of the linear array with the local signal;

[0068] Step 2) Use the relevant results obtained in Step 1) to estimate the coarse delay difference between channels 1 and 2;

[0069] Step 3) Estimate the multi-channel phase difference of the received signal using a notch filter;

[0070] Step 4) Calculate the ambiguity number list based on the multi-channel phase difference;

[0071] Step 5) Use the coarse time delay difference obtained in Step 2) and the fuzzy table obtained in Step 4) to solve the fuzziness of the phase difference;

[0072] Step 6) Use the unambiguous phase difference obtained in step 5) to perform direction finding.

[0073] Preferably, step 1) of the present invention includes:

[0074] Step 1-1) Perform an M-order bandpass filter on the received signal s(n) of the linear array; the M-order bandpass filter process is as follows:

[0075]

[0076] Among them, s i (n) represents the discrete received signal of the i-th channel, where n is the number of sampling points, M represents the filter order, and the coefficients b m Let m represent the m-th filter coefficient. An M-order filter has a total of M+1 coefficients, where 0 ≤ m ≤ M.

[0077] Steps 1-2) Generate a local single-frequency signal based on parameters such as signal frequency and sampling rate; the local single-frequency signal is shown below:

[0078] s l (n)=exp{j·2πf c n·T s}

[0079] Where j is the imaginary sign, f c T is the center carrier frequency of the received signal. s is the sampling rate; exp{·} is the complex exponentiation operation.

[0080] Steps 1-3) Perform pulse compression on the bandpass filtering result using the local signal; the pulse compression formula is shown below:

[0081]

[0082] Where, x i (n) represents the bandpass filtering result of the i-th channel, sl (N-(mn)) represents the translation signal of the local signal, and n1 represents the local signal relative to x. i (n) The number of points to be translated, where N represents the length of the signal, and y i (n1) represents the pulse compression result of the i-th channel.

[0083] Preferably, step 2) of the present invention includes:

[0084] Step 2-1) Find the peak value of the pulse compression result segment by segment and compare it with the pre-set threshold to find the position of the signal;

[0085] Step 2-2) Find the maximum value of the pulse compression result, estimate the relative time delay, and calculate the coarse time delay difference.

[0086] Preferably, step 3) of the present invention includes:

[0087] Based on the signal position obtained in step 2), obtain the signal data segment, use a notch filter to calculate the phase of each channel, and then calculate the phase difference between channels 1 and 2 and channels 1 and 3.

[0088] Preferably, step 4) of the present invention includes:

[0089] Step 4-1) Calculate the time delay difference range of channels 1 and 3 based on the target azimuth range, and then calculate the ambiguity number range of the phase difference between channels 1 and 3; the ambiguity number range of channels 1 and 3 (upper limit n) 13max The lower limit is -n 13max The calculation formula is as follows:

[0090]

[0091] in, L represents the target's maximum azimuth angle. 13 The distance between the 1st and 3rd elements is represented by N, where N represents the signal length and P represents the distance between the 1st and 3rd elements. i (n1) represents the pulse compression result of the i-th channel, and floor() represents the floor function.

[0092] Step 4-2) Calculate the list of phase difference ambiguity numbers for channels 1 and 2 based on the ambiguity number ranges for channels 1 and 3;

[0093]

[0094] Where, p 13 p represents the phase difference between the principal values ​​of channels 1 and 3. 12 n represents the phase difference between the principal values ​​of channels 1 and 2. 13,j This represents the j-th ambiguity number of the phase difference between channels 1 and 3, where n is the number of ambiguities. 12,j L represents the j-th ambiguity number of the phase difference between channels 1 and 2 after matching. 12This indicates the spacing between primitives 1 and 2, and round() represents the rounding function.

[0095] Preferably, step 5) of the present invention includes:

[0096] Step 5-1) Calculate the coarse ambiguity number of the phase difference based on the coarse delay difference between channels 1 and 2; the formula for calculating the coarse ambiguity number is as follows:

[0097]

[0098] in, To obtain the coarse delay difference between channels 1 and 2 in step 2), The coarse fuzzy number represents the phase difference between channels 1 and 2.

[0099] Step 5-2) Search for the accurate fuzzy number based on the coarse fuzzy number of the phase difference between channels 1 and 2 and the fuzzy number list obtained in step 4); the formula for calculating the accurate fuzzy number is as follows:

[0100]

[0101] Where C is the list of phase difference ambiguity numbers for channels 1 and 2 obtained in step 4).

[0102] Step 5-3) Calculate the unambiguous phase difference based on the ambiguity numbers of channels 1 and 2; the formula for the unambiguous phase difference is as follows:

[0103] P 12 =p 12 +n 12 2π

[0104] Among them, P 12 For channels 1 and 2, there is no ambiguity phase difference, n 12 The ambiguity number is the phase difference between channels 1 and 2.

[0105] Preferably, step 6) of the present invention includes:

[0106] Step 6-1) Calculate the high-precision time delay difference based on the unambiguous phase difference between channels 1 and 2 obtained in step 5); the direction finding formula is as follows:

[0107]

[0108] Among them, t 12 This indicates the high-precision time delay difference between channels 1 and 2.

[0109] Step 6-2) Calculate the target azimuth based on the high-precision time delay difference; the direction finding formula is as follows:

[0110]

[0111] Here, phi represents the target's orientation relative to the receiving linear array, with the right side being positive and the left side being negative.

[0112] Example 2

[0113] An underwater single-frequency signal direction finding system of the present invention includes:

[0114] The signal correlation processing module is used to correlate the received signal of the linear array with the local single-frequency signal;

[0115] The coarse delay difference estimation module is used to estimate the coarse delay difference using the correlation results obtained from the signal correlation processing module.

[0116] The phase difference estimation module is used to estimate the multi-channel phase difference of the received signal using a notch filter.

[0117] The fuzzy number calculation module is used to calculate a list of fuzzy numbers based on the phase difference of multiple channels;

[0118] The unambiguous phase difference calculation module is used to solve for the unambiguous phase difference using the coarse time delay difference obtained from the coarse time delay difference estimation module and the fuzzy number list obtained from the fuzzy number calculation module; and

[0119] The direction finding module is used to perform direction finding using the unambiguous phase difference obtained by the unambiguous phase difference calculation module.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An underwater single-frequency signal direction finding method, comprising: Step 1) Correlate the received signal of the linear array with the local single-frequency signal; The linear array includes a first element, a second element, and a third element, wherein the first element and the third element are spaced apart, and the first element and the second element are spaced apart; the signals received by the first element, the second element, and the third element are processed in the first channel, the second channel, and the third channel, respectively. Step 2) Using the relevant results obtained in Step 1), estimate the coarse time delay difference; Step 3) Estimate the multi-channel phase difference of the received signal using a notch filter; Step 4) Calculate the ambiguity number list based on the multi-channel phase difference; Step 4) includes: Step 4-1) Calculate the time delay difference range between the first and third channels based on the target azimuth range, and then calculate the ambiguity number range of the phase difference between the first and third channels; the upper limit of the ambiguity number of the phase difference between the first and third channels. The calculation formula is as follows: in, Indicates the target's maximum azimuth angle. This represents the distance between the first and third primitives. The value represents the speed of sound propagation in water, and floor() represents the floor function; the lower limit of the phase difference ambiguity number between the first and third channels is... ; Step 4-2) Calculate the phase difference ambiguity number list for the first and second channels based on the phase difference ambiguity number range of the first and third channels; where, the phase difference ambiguity number range of the first and third channels is... fuzzy number Represented as: in, The phase difference between the principal values ​​of the first and third channels. The phase difference between the principal values ​​of the first and second channels. This indicates the phase difference between the first and third channels. A vague number, The interval between the first and second primitives is represented by , and round() represents the rounding function; Step 5) Use the coarse time delay difference obtained in Step 2) and the list of fuzzy numbers obtained in Step 4) to solve for the unfuzzy phase difference; Step 6) Use the unambiguous phase difference obtained in step 5) to perform direction finding.

2. The underwater single-frequency signal direction finding method according to claim 1, characterized in that, The relevant results obtained in step 1) include the pulse compression results for each channel; Among them, the first i Pulse compression results of the channel Represented as: in, Indicates the first The bandpass filtering result of the channel received signal. Indicates local single-frequency signal Translation signal, m Indicates local single-frequency signal Compared to The number of points translated, Indicates local single-frequency signal Length, This represents the number of sampling points.

3. The underwater single-frequency signal direction finding method according to claim 2, characterized in that, The first The bandpass filtering result of the channel received signal is expressed as follows: in, For the first Discrete received signal of the channel, coefficients Indicates the first Each filter coefficient M This indicates the order of the bandpass filter. There are a total of order filters One coefficient; in, j It is the symbol for imaginary numbers. The center carrier frequency of the received signal. Sampling rate; This is for complex exponentiation.

4. The underwater single-frequency signal direction finding method according to claim 2, characterized in that, Step 2) includes: Step 2-1) Find the peak value of the pulse compression result segment by segment and compare it with the pre-set threshold to find the position of the received signal; Step 2-2) Find the peak value of the pulse compression result, estimate the relative time delay between the received signal and the local signal, and calculate the coarse time delay difference.

5. The underwater single-frequency signal direction finding method according to claim 4, characterized in that, Step 3) includes: Based on the position of the received signal obtained in step 2-1), the received signal data segment is obtained, the phase of each channel is calculated using a notch filter, and then the phase difference between the first channel and the second channel, as well as the phase difference between the first channel and the third channel, are calculated.

6. The underwater single-frequency signal direction finding method according to claim 1, characterized in that, Step 5) includes: Step 5-1) Calculate the coarse ambiguity number of the phase difference between the first and second channels based on the coarse time delay difference obtained in Step 2). : in, This represents the coarse delay difference between the first and second channels. Step 5-2) Based on the coarse fuzzy number of the phase difference between the first and second channels Search for the accurate fuzzy number from the list of fuzzy numbers obtained in step 4). Calculate the accurate blur number for the first and second channels: in, For step 4), obtain the list of phase difference ambiguity numbers for the first and second channels; Step 5-3) Calculate the unambiguous phase difference based on the coarse ambiguity numbers of the first and second channels; the formula for the unambiguous phase difference is as follows: in, There is no blurring phase difference between the first and second channels. The ambiguity number is the phase difference between the first and second channels.

7. The underwater single-frequency signal direction finding method according to claim 6, characterized in that, Step 6) includes: Step 6-1) Calculate the high-precision time delay difference between the first and second channels based on the unambiguous phase difference obtained in Step 5). : in, This indicates the high-precision time delay difference between channels 1 and 2; Step 6-2) Calculate the target's azimuth relative to the receiving linear array based on the high-precision time delay difference. : Among them, orientation A positive value indicates the right side, and a negative value indicates the left side.

8. An underwater single-frequency signal direction finding system, characterized in that, include: The signal correlation processing module is used to correlate the received signal of the linear array with the local single-frequency signal; The linear array includes a first element, a second element, and a third element, wherein the first element and the third element are spaced apart, and the first element and the second element are spaced apart; the signals received by the first element, the second element, and the third element are processed in the first channel, the second channel, and the third channel, respectively. The coarse delay difference estimation module is used to estimate the coarse delay difference using the correlation results obtained from the signal correlation processing module. The phase difference estimation module is used to estimate the multi-channel phase difference of the received signal using a notch filter. The fuzzy number calculation module is used to calculate a list of fuzzy numbers based on the phase difference of multiple channels. The specific steps include: The time delay difference range between the first and third channels is calculated based on the target azimuth range, and then the ambiguity number range of the phase difference between the first and third channels is calculated; the upper limit of the ambiguity number of the phase difference between the first and third channels is also calculated. The calculation formula is as follows: in, Indicates the target's maximum azimuth angle. This represents the distance between the first and third primitives. The value represents the speed of sound propagation in water, and floor() represents the floor function; the lower limit of the phase difference ambiguity number between the first and third channels is... ; Calculate the ambiguity number list for the phase difference between the first and second channels based on the ambiguity number range of the phase difference between the first and third channels; where the ambiguity number list for the phase difference between the first and second channels is... fuzzy number Represented as: in, The phase difference between the principal values ​​of the first and third channels. The phase difference between the principal values ​​of the first and second channels. This indicates the phase difference between the first and third channels. A vague number, The interval between the first and second primitives is represented by , and round() represents the rounding function; The unambiguous phase difference calculation module is used to solve for the unambiguous phase difference using the coarse time delay difference obtained from the coarse time delay difference estimation module and the fuzzy number list obtained from the fuzzy number calculation module; and The direction finding module is used to perform direction finding using the unambiguous phase difference obtained by the unambiguous phase difference calculation module.

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