A horizontal array range spectrum estimation method and product based on azimuth dictionary table query

Abstract

The present invention discloses a method and product for estimating the range spectrum of a horizontal array based on an azimuth angle dictionary table query. The method comprises: establishing a correspondence between the true azimuth angle of a target at different spatial locations and the azimuth angle obtained by plane wave processing of the horizontal array in polar coordinate form to obtain an azimuth angle dictionary table; performing spatial spectrum synthesis on the horizontal array received data at a set scanning interval using a plane wave array signal processing method to obtain an azimuth spectrum synthesized from the horizontal array data; obtaining an estimate of the target azimuth in the azimuth spectrum using the amplitude ratio method; presetting the target distance relative to the horizontal array in a near-to-far manner, and querying the azimuth angle dictionary table to extract the target azimuth query results at each preset distance; calculating the energy spectrum at each preset distance using a simple normal wave processing method based on the preset distance to obtain a range spectrum; and performing a maximum value position query to obtain the target distance value relative to the horizontal array. This invention provides a method for improving the accuracy of horizontal array distance estimation.

Description

Technical Field

[0001] The present invention relates to the field of sonar signal processing, and in particular to a horizontal array range spectrum estimation method and product based on azimuth angle dictionary table query. Background Art

[0002] In naval battlefields, there are numerous active sonar signals, including underwater communication sonar, low-frequency submarine detection sonar, high-frequency mine detection sonar, and torpedo homing sonar, as well as navigational noise signals radiated by surface ships, submarines, torpedoes, and unmanned underwater vehicles. Active sonar signals primarily take the form of narrowband continuous wave (CW), broadband linear frequency modulation (LFM), and broadband hyperbolic frequency modulation (HFM). Ship-radiated noise primarily consists of broadband signals with low-frequency line spectrum characteristics. If these signals are intercepted and fully utilized through intercepted signal detection and processing technology, the target detection range can be increased, enabling target identification and location of the launch platform.

[0003] Surface ships can intercept the active homing signals of incoming torpedoes and estimate their location, enabling them to take effective countermeasures. Submarines can use intercepted active sonar signals to conduct long-range surveillance and attack against ships. Submerged mines can intercept active signals emitted by minehunting sonars and estimate their range, improving their survival probability and combat effectiveness. Therefore, using intercepted signals to detect and track underwater targets has become an important means of acquiring information about future underwater combat situations.

[0004] Uniform linear array (ULA) sonar elements are arranged in a straight line with equal spacing, resulting in a simple structure and easy engineering implementation. They are widely used in surface ship sonar, submarine sonar, and shore-based array sonar. A passive towed linear array sonar (TLAS) employing a ULA array consists of hydrophones embedded in an electrical (optical) cable to form a linear array (in practical applications). The cable is towed behind the stern of a ship. This type of sonar is primarily used to detect submarine radiated noise for long-range surveillance, positioning, and identification. Its advantages include large array size, low operating frequency, long detection range, and excellent concealment, making it widely used on naval vessels.

[0005] Passive positioning using a passive horizontal towed linear array sonar primarily involves estimating the target's position and range. In the far-field plane wave model, the sound rays are assumed to propagate as plane waves, and the distances from the sound source to each array element are approximately equal. The time delay between adjacent array elements receiving signals in a uniform linear array sonar is related only to the sound source's position and not to its distance from the array. Therefore, passive target positioning methods based on the far-field model can only effectively estimate the target's position. When the sound source does not meet the far-field condition, that is, when it is in the near-field environment of the array, the distances from the sound source to each array element vary significantly and can no longer be approximated as equal. The time delay between adjacent array elements receiving signals depends not only on the sound source's position but also on its distance from the array. In this case, a simple normal wave model that includes both target position and range information should be used for modeling.

[0006] Existing research on passive ranging of underwater acoustic targets primarily includes three-element passive ranging, passive positioning based on modulus basis matching or matching fields, passive ranging based on waveguide invariant theory, near-field target ranging using focused beamforming, and near-field target ranging based on azimuth-first and range-later techniques. Passive ranging techniques based on waveguide invariant theory require integration with ocean acoustic propagation theory, resulting in complex computational processes and stringent requirements for the marine environment. These techniques generally require the presence of waveguide interference to achieve target ranging. Focused beamforming-based passive ranging techniques, based on a near-field simple normal wave propagation array receiving data model, achieve target location through a two-dimensional search of spatial direction and range. These methods require a considerable amount of computation and, in systems with high real-time requirements, leave room for improvement. Azimuth-first and range-later techniques first estimate the approximate target azimuth using plane wave technology and then estimate the distance based on this estimated azimuth. These techniques place high demands on target azimuth accuracy; errors in target azimuth significantly impact the accuracy of target range estimation using these techniques. Summary of the Invention

[0007] The purpose of the present invention is to overcome the defects of the prior art and propose a horizontal array range spectrum estimation method and product based on azimuth angle dictionary table query.

[0008] In view of this, the present invention proposes a horizontal array range spectrum estimation method based on azimuth angle dictionary table query, the method comprising:

[0009] Step 1: Establish the correspondence between the true azimuth of the target at different positions in space and the azimuth obtained by horizontal array plane wave processing in polar coordinate form to obtain the azimuth dictionary table;

[0010] Step 2: Perform spatial spectrum synthesis on the horizontal array received data at a set angle scanning interval using a plane wave array signal processing method to obtain an azimuth spectrum synthesized from the horizontal array data;

[0011] Step 3: Based on the azimuth spectrum synthesized from the horizontal array data, obtain the estimated result of the target azimuth in the azimuth spectrum using the amplitude ratio method;

[0012] Step 4: Preset the target's relative horizontal array distance from near to far, and retrieve the target azimuth query results at each preset distance by querying the azimuth dictionary table;

[0013] Step 5: Use the target azimuth query result according to the preset distance and combine it with the simple normal wave processing method to obtain the energy spectrum at each preset distance to obtain the range spectrum;

[0014] Step 6: Based on the obtained distance spectrum, query the maximum position. The obtained position is the distance value of the target relative to the horizontal array.

[0015] Preferably, the azimuth angle dictionary table AngleTable(R,θ) obtained in step 1 is:

[0016]

[0017] Among them, n∈[1,N] is the array element number, N is the total number of horizontal array elements, is the grid position (x, y) relative to the nth array element position (x n ,y n ) distance, x=Rcos(θ), y=Rsin(θ), θ∈[0°,180°] is the grid division angle range, R∈[R min ,R max ] is the distance range for grid division; is the phase difference of each array element relative to the first array element obtained by plane wave processing, θ1∈[0°,180°] is the scanning azimuth angle of plane wave processing, the direction from the tail to the head of the array is 0°, and the direction from the head to the tail is 180°, c is the sound speed, f is the processing frequency, d is the distance between adjacent array elements, exp(·) is the exponential function,

[0018] Preferably, the azimuth spectrum B(θ) obtained in step 2 is:

[0019]

[0020] Among them, S n (f) is the target radiation signal received by the nth array element, f is the signal frequency, is the phase difference of each array element relative to the first array element obtained by plane wave processing, θ∈[0°,180°] is the scanning azimuth angle of plane wave processing, the direction from the tail to the front of the array is 0°, and the direction from the front to the tail of the array is 180°, c is the speed of sound, exp(·) is the exponential function,

[0021] Preferably, the estimation result obtained in step 3 is for:

[0022]

[0023] in, is the position corresponding to the maximum value of the azimuth spectrum, B L is the energy difference between the beam corresponding to the maximum position and the beam on the left, B R is the energy difference between the beam corresponding to the maximum position and the beam on the right, B(θ) is the azimuth spectrum result.

[0024] Preferably, the target azimuth query results at each preset distance obtained in step 4 are for:

[0025]

[0026] Among them, θ∈[0°,180°] is the grid division angle range, AngleTable(R,θ) is the azimuth angle dictionary table, is the estimated result obtained in step 3.

[0027] Preferably, the distance spectrum B(R) obtained in step 5 is:

[0028]

[0029] in, The target position (x, y) is relative to the nth array element position (x n ,y n ), c is the speed of sound, exp(·) is the exponential function,

[0030] Preferably, the target relative horizontal array distance value obtained in step 6 is for:

[0031]

[0032] Where B(R) is the distance spectrum obtained in step 5.

[0033] In another aspect, the present invention provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the method according to claim 1. Compared with the prior art, the present invention has the following advantages:

[0034] Based on the invariance of the difference between the target's azimuth relative to the horizontal array and the azimuth obtained by horizontal array plane wave processing, this method establishes a correspondence table (called an azimuth dictionary table) between the target's true azimuth at different spatial positions and the azimuth obtained by horizontal array plane wave processing in polar coordinate form. Then, by querying the azimuth dictionary table, the target azimuth query results at each preset distance can be accurately extracted, and the energy spectrum at each preset distance can be obtained (the entire result is called a range spectrum). Based on this range spectrum, an accurate estimation of the target distance can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the horizontal array sonar structure used in an embodiment of the present invention;

[0036] Figure 2 This is a diagram showing the positions of the elements of a horizontal line array used in a numerical simulation verification experiment of an embodiment of the present invention;

[0037] Figure 3 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 5 km and the azimuth θ = 0° to 180°;

[0038] Figure 4 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 10 km and the azimuth θ = 0° to 180°;

[0039] Figure 5 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 20 km and the azimuth θ = 0° to 180°;

[0040] Figure 6 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 5km and the azimuth θ = 30°;

[0041] Figure 7 The target is located at a distance of R = 5 km and an azimuth of θ = 30°, and the target azimuth query results at each preset distance are obtained by querying the azimuth dictionary table within a preset distance of R = 2 km to 30 km.

[0042] Figure 8 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 5km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0043] Figure 9The target is located at a distance of R = 5 km and an azimuth of θ = 30°, and the range spectrum is obtained by the method of the present invention.

[0044] Figure 10 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 10 km and the azimuth θ = 30°;

[0045] Figure 11 The target is located at a distance of R = 10 km and an azimuth of θ = 30°, and the azimuth angle dictionary table is searched for the preset distances R = 2 km to 30 km, and the target azimuth angle query results at each preset distance are obtained;

[0046] Figure 12 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 10 km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0047] Figure 13 The target is located at a distance of R = 10 km and an azimuth of θ = 30°, and the range spectrum is obtained by the method of the present invention.

[0048] Figure 14 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 20 km and the azimuth θ = 30°;

[0049] Figure 15 The target is located at a distance of R = 20 km and an azimuth of θ = 30°, and the azimuth angle dictionary table is searched for the preset distances R = 2 km to 30 km, and the target azimuth angle query results at each preset distance are obtained;

[0050] Figure 16 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 20 km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0051] Figure 17 This is a range spectrum obtained by the method of the present invention when the target is located at a distance R = 20 km and an azimuth θ = 30°, obtained from a numerical simulation verification experiment of an embodiment of the present invention. DETAILED DESCRIPTION

[0052] To address the passive positioning issues of passive towed linear array sonars, the present invention proposes a range spectrum estimation method based on azimuth angle dictionary lookup. Based on the resolvability of the azimuth difference between the target's radiated simple normal wave and the horizontal array's plane wave processing, this method uses trigonometric geometry to achieve real-time correction of the target azimuth angle obtained through plane wave processing. This corrected azimuth angle is then combined with simple normal wave processing to calculate the energy spectrum at each preset distance (the entire result is referred to as the range spectrum). This resulting range spectrum allows for accurate estimation of target distance. This invention provides a means to improve the accuracy of target range estimation using horizontal arrays.

[0053] Before describing the method of the present invention in detail, the horizontal array to which the method of the present invention is applicable is first described. Figure 1 The figure shows the structure of a horizontal array sonar system, which mainly includes five components: processing and display unit 1, retractable mechanism 2, cable outlet 3, streamer 4, and horizontal array 5. The horizontal array 5 is connected to the deck cable located on the retractable mechanism 2 via the streamer 4. The signals received by the horizontal array 5 are transmitted to the processing and display unit 1.

[0054] The method of the present invention is further described below.

[0055] 1. Description of the target's near and far fields relative to the horizontal array

[0056] According to the distance between the target signal source and the receiving array, the target signal source can usually be divided into far-field source and near-field source. When the target is a far-field signal source, the distance relationship between the target and the receiving array satisfies r>>2D 2 / λ, (D=(M-1)d represents the array aperture, λ is the wavelength of the incident signal), that is, the spatial observation signal is located in the Fraunhofer region of the array aperture, that is, the far field region. At this time, the array receiving signal satisfies the plane wave assumption, the amplitude of the received signal of each array element is the same, and the phase difference is only related to the incident angle of the signal; when the target is a near-field source signal, the distance relationship between the target and the receiving array satisfies r∈[0.62(D 3 / λ) 0.5 ,2D 2 / λ], that is, the spatial observation signal source is located in the Fresnel region of the array aperture, that is, the near-field region. At this time, the sound wave is incident along the simple normal wave, and the phase difference is determined by the incident signal angle and distance.

[0057] Because the target position is unknown, the acoustic path difference between the received signals of each array element at different locations is a combination of range and azimuth. Using far-field processing will result in a certain difference between the target azimuth obtained by the horizontal array and the actual azimuth. To address this, we can use trigonometric geometry to implement real-time corrections to the target azimuth obtained by plane wave processing, based on the resolvability of the azimuth difference between the target's radiated simple normal wave and the horizontal array's plane wave processing.

[0058] 2. Analysis of azimuth estimation errors of each sub-array

[0059] The near-field sound source is located in the Fresnel zone received by the array, that is, r∈[0.62(D 3 / λ) 0.5 ,2D 2 / λ]; the complex envelope amplitudes of the signals received by different array elements are approximately equal, that is, r k / r mk ≈1, where r k is the distance from the kth target signal source to the array reference point, r mk is the distance from the kth target signal source to the mth array element; and the corresponding phase difference in this area can be approximated by the second-order Taylor expansion, that is:

[0060]

[0061] Where θ k is the azimuth angle of the kth target signal source relative to the array, and d is the distance between adjacent array elements.

[0062] Therefore, the near-field steering vector can be simplified into the following approximate form:

[0063] a N (r k ,θ k )≈[1,exp(-j(mα k +m 2 β k )),…,exp(-j((M-1)α k +(M-1) 2 β k ))] T

[0064]

[0065] The above equation is often called the Frenel approximation. Its significance lies in stating that in the short-range region (Fresnel zone) of the array reception, the wavefront of the simple normal wave is no longer a plane but a quadratic surface. If plane waves are used for azimuth estimation in practice, azimuth estimation errors are inevitably introduced.

[0066] 3. Correlation analysis of different models

[0067] The similarity between a plane wave and a normal wave is closely related to the specific position of the sound source relative to the receiving array. The stationary phase principle can be used to give an approximate solution to the correlation coefficient. A near-field source at a certain position in space has a strong correlation coefficient with a far-field source in a certain width fan area "behind" it, and a weak correlation with a far-field source far away from this angle. The physical quantity describing the correlation between the guiding vectors of a plane wave and a normal wave is redefined as follows:

[0068]

[0069] Where, α F (θ F ) and α N (r, θ) are the array flow patterns of the far-field and near-field targets respectively. Based on the model assumptions of far-field plane waves and near-field normal waves, the array flow pattern can be expressed as:

[0070]

[0071] The parameter ρ(r,θ) represents the maximum correlation coefficient between the near-field sound source located at (r,θ) and the far-field space. As ρ(r,θ) increases, the simple normal waveguide vector of the near-field source approaches the far-field plane waveguide vector at a certain angle. When ρ(r,θ)→1, even if the condition of r→∞ is not met, the sound source at this location can be considered equivalent to the far-field sound source at a certain angle.

[0072] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0073] Example 1

[0074] This embodiment provides a distance spectrum estimation method based on azimuth angle dictionary table query.

[0075] Based on the invariance of the difference between the target's azimuth relative to the horizontal array and the azimuth obtained by plane wave processing of the horizontal array, this method establishes a correspondence table (called an azimuth dictionary table) between the target's true azimuth at different spatial positions and the azimuth obtained by plane wave processing of the horizontal array in polar coordinate form. Secondly, the plane wave array signal processing method is used to perform spatial spectrum synthesis on the horizontal array received data at a scanning interval of 0.1° to obtain the synthesized azimuth spectrum of the horizontal array data. Based on the synthesized azimuth spectrum of the horizontal array data, the amplitude ratio method is used to obtain the estimation result of the target azimuth in the azimuth spectrum. Then, the target azimuth query result at each preset distance is extracted by querying the azimuth dictionary table. Finally, the energy spectrum at each preset distance is obtained by combining the simple normal wave processing method (the entire result is called the range spectrum). Based on this range spectrum, the target distance can be accurately estimated.

[0076] Specifically, the following steps are included:

[0077] Step 1) Create a corresponding relationship table (called azimuth angle dictionary table) AngleTable(R,θ) between the target's true azimuth angle at different locations in space and the azimuth angle obtained by horizontal array plane wave processing in polar coordinate form (grid spacing is 1m×0.1°).

[0078]

[0079] Among them, n∈[1,N] is the array element number, N is the total number of horizontal array elements, is the grid position relative to the nth array element position (x n ,y n ) distance, x=R cos(θ), y=R sin(θ), θ∈[0°,180°] is the grid division angle range, R∈[R min ,R max ] is the distance range for grid division; is the phase difference of each array element relative to the first array element (element 1) obtained by plane wave processing, θ1∈[0°,180°] is the scanning azimuth angle of the plane wave processing, the direction from the tail to the front of the array is 0°, and the direction from the front to the tail of the array is 180°, c is the sound speed, f is the processing frequency, d is the distance between adjacent array elements, exp(·) is the exponential function,

[0080] Step 2) Perform spatial spectrum synthesis on the horizontal array at a scanning interval of 0.1° using a plane wave array signal processing method to obtain an azimuth spectrum B(θ) synthesized from the horizontal array data.

[0081]

[0082] Among them, S n (f) is the target radiation signal received by the nth array element, f is the signal frequency (the processing frequency is equal to it), is the phase difference of each array element relative to the first array element (element 1) obtained by plane wave processing, θ∈[0°,180°] is the scanning azimuth angle of the plane wave processing, the direction from the tail to the front of the array is 0°, and the direction from the front to the tail of the array is 180°, c is the speed of sound, exp(·) is the exponential function,

[0083] Step 3) Synthesize the azimuth spectrum result B(θ) based on the horizontal array data, and obtain the estimated result of the target azimuth in the azimuth spectrum according to the amplitude ratio method

[0084]

[0085] in, is the position corresponding to the maximum value of the azimuth spectrum,

[0086] Step 4) Preset the target relative horizontal array distance R∈[R min ,R max ], and extract the target azimuth query results at each preset distance by querying the azimuth dictionary table AngleTable(R,θ)

[0087]

[0088] Among them, θ∈[0°,180°] is the grid division angle range.

[0089] Step 5) Use the target azimuth query result The energy spectrum (the whole result is called the distance spectrum) B(R) at each preset distance is obtained by combining the simple normal wave processing method according to the preset distance; where R min is the preset minimum distance, R max To preset the maximum distance, the length of one step is ΔR.

[0090]

[0091] in, The target position (x, y) is relative to the nth array element position (x n ,y n )distance, c is the speed of sound, exp(·) is the exponential function,

[0092] Step 6) Based on the obtained distance spectrum B(R), the maximum position is searched. This position is the distance value of the target relative to the horizontal array.

[0093]

[0094] Example 2

[0095] The embodiment of the present invention may further provide a computer program product, including a computer program / instruction. When the computer program / instruction is executed by a processor, each step in the above method embodiment can be implemented.

[0096] Experimental analysis

[0097] In order to further verify that the method of the present invention can effectively realize the accurate extraction of target distance information, the following numerical simulation analysis is performed.

[0098] In the numerical simulation experiment, the Figure 2The position diagram of each element of the horizontal array is shown. The spacing between adjacent elements of the horizontal array is d = 8m, the number of elements in the horizontal array is N = 128, and the effective aperture of the horizontal array is 1016m. This simulation process assumes that the target radiation signal is a single-frequency signal of f = 93Hz, the distance between the target position and the first element of the horizontal array is R, and the azimuth is θ.

[0099] Figure 3 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 5 km and the azimuth θ = 0° to 180°;

[0100] Figure 4 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 10 km and the azimuth θ = 0° to 180°;

[0101] Figure 5 The target azimuth angle obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 20 km and the azimuth θ = 0° to 180°;

[0102] Figure 6 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 5km and the azimuth θ = 30°;

[0103] Figure 7 The target is located at a distance of R = 5 km and an azimuth of θ = 30°, and the target azimuth query results at each preset distance are obtained by querying the azimuth dictionary table within a preset distance of R = 2 km to 30 km.

[0104] Figure 8 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 5km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0105] Figure 9 The target is located at a distance of R = 5 km and an azimuth of θ = 30°, and the range spectrum is obtained by the method of the present invention.

[0106] Figure 10 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 10 km and the azimuth θ = 30°;

[0107] Figure 11The target is located at a distance of R = 10 km and an azimuth of θ = 30°, and the azimuth angle dictionary table is searched for the preset distances R = 2 km to 30 km, and the target azimuth angle query results at each preset distance are obtained;

[0108] Figure 12 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 10 km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0109] Figure 13 The target is located at a distance of R = 10 km and an azimuth of θ = 30°, and the range spectrum is obtained by the method of the present invention.

[0110] Figure 14 The azimuth spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained by using the far-field plane wave processing method when the target is located at a distance R = 20 km and the azimuth θ = 30°;

[0111] Figure 15 The target is located at a distance of R = 20 km and an azimuth of θ = 30°, and the azimuth angle dictionary table is searched for the preset distances R = 2 km to 30 km, and the target azimuth angle query results at each preset distance are obtained;

[0112] Figure 16 The range spectrum obtained by the numerical simulation verification experiment of the embodiment of the present invention is obtained when the target is located at a distance R = 20 km and the azimuth θ = 30°, using the azimuth-first and then distance estimation method;

[0113] Figure 17 This is a range spectrum obtained by the method of the present invention when the target is located at a distance R = 20 km and an azimuth θ = 30°, obtained from a numerical simulation verification experiment of an embodiment of the present invention.

[0114] From the simulation results, it can be seen that by querying the azimuth angle dictionary table for the target azimuth angle, the obtained range spectrum synthesis result and the distance estimation result obtained based on it are more accurate.

[0115] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art 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 are intended to be encompassed by the claims of the present invention.

Claims

1. A method for estimating horizontal array range spectrum based on azimuth angle dictionary table query, the method comprising: Step 1: Establish the correspondence between the true azimuth of the target at different positions in space and the azimuth obtained by horizontal array plane wave processing in polar coordinate form to obtain the azimuth dictionary table; Step 2: Perform spatial spectrum synthesis on the horizontal array received data at a set angle scanning interval according to the plane wave array signal processing method to obtain an azimuth spectrum synthesized from the horizontal array data; Step 3: Based on the azimuth spectrum synthesized from the horizontal array data, obtain the estimated result of the target azimuth in the azimuth spectrum using the amplitude ratio method; Step 4: Preset the target's relative horizontal array distance from near to far, and retrieve the target azimuth query results at each preset distance by querying the azimuth dictionary table; Step 5: Use the target azimuth query result according to the preset distance and combine it with the simple normal wave processing method to obtain the energy spectrum at each preset distance to obtain the range spectrum; Step 6: Based on the obtained distance spectrum, query the maximum position. The obtained position is the distance value of the target relative to the horizontal array.

2. The horizontal array range spectrum estimation method based on azimuth angle dictionary table query according to claim 1 is characterized in that: The azimuth angle dictionary table AngleTable(R,θ) obtained in step 1 is: Among them, n∈[1,N] is the array element number, N is the total number of horizontal array elements, is the grid position (x, y) relative to the nth array element position (x n ,y n ) distance, x=Rcos(θ), y=Rsin(θ), θ∈[0°,180°] is the grid division angle range, R∈[R min ,R max ] is the grid division distance range, R min ,R max are the preset minimum distance and maximum distance respectively, and R is the target relative horizontal array distance; is the phase difference of each array element relative to the first array element obtained by plane wave processing, θ1∈[0°,180°] is the scanning azimuth angle of plane wave processing, the direction from the tail to the head of the array is 0°, and the direction from the head to the tail is 180°, c is the speed of sound, f is the signal frequency, d is the distance between adjacent array elements, exp(·) is the exponential function, 3. The horizontal array range spectrum estimation method based on azimuth angle dictionary table query according to claim 1 is characterized in that: The azimuth spectrum B(θ) obtained in step 2 is: Among them, S n (f) is the target radiation signal received by the nth array element, f is the signal frequency, is the phase difference of each array element relative to the first array element obtained by plane wave processing, θ1∈[0°,180°] is the scanning azimuth angle of plane wave processing, the direction from the tail to the head of the array is 0°, and the direction from the head to the tail is 180°, c is the speed of sound, exp(·) is the exponential function, N is the total number of horizontal array elements.

4. The horizontal array range spectrum estimation method based on azimuth angle dictionary table query according to claim 1 is characterized in that: The estimation result obtained in step 3 for: in, is the position corresponding to the maximum value of the azimuth spectrum, B L is the energy difference between the beam corresponding to the maximum position and the beam on the left, B R is the energy difference between the beam corresponding to the maximum position and the beam on the right, B(θ) is the azimuth spectrum result, and θ∈[0°,180°] is the grid division angle range.

5. The method for estimating horizontal array range spectrum based on azimuth angle dictionary table query according to claim 1, characterized in that: The target azimuth query results at each preset distance obtained in step 4 for: Among them, θ∈[0°,180°] is the grid division angle range, AngleTable(R,θ) is the azimuth angle dictionary table, is the estimation result obtained in step 3, R is the relative horizontal array distance of the target, and θ∈[0°,180°] is the grid division angle range.

6. The method for estimating horizontal array range spectrum based on azimuth angle dictionary table query according to claim 1, characterized in that: The distance spectrum B(R) obtained in step 5 is: in, The target position (x, y) is relative to the nth array element position (x n ,y n ), c is the speed of sound, exp(·) is the exponential function, S n (f) is the target radiation signal received by the nth array element, f is the signal frequency, is the target azimuth query result at the preset distance, and R is the target relative horizontal array distance.

7. The method for estimating horizontal array range spectrum based on azimuth angle dictionary table query according to claim 1, characterized in that: The target relative horizontal array distance value obtained in step 6 for: Where B(R) is the range spectrum obtained in step 5, and R is the distance of the target relative to the horizontal array.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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