A method and device for estimating direction of arrival

Abstract

The invention is based on an adaptive null trap array, which is divided into a reference array and an auxiliary array, both of which receive incident signals. The null trap array weight vector is solved for the auxiliary array according to a minimum mean square error criterion, the weight vector is optimized by using a variable step size idea, the iterative update speed of the weight is accelerated, and the null trap array weight vector is further optimized by using a deviation compensation idea, so that it is converted from a biased estimation to an unbiased estimation, thereby improving the arrival azimuth estimation performance. Compared with the existing null trap array azimuth estimation method of the same type, the invention can not only obtain better estimation accuracy, but also has a lower RMSE under a low signal-to-noise ratio, and the invention can always maintain a low RMSE result as the signal-to-noise ratio increases.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a direction-of-arrival estimation method and a device thereof. Background Art

[0002] Direction of arrival estimation is an important research direction in array signal processing. It has been widely used in the fields of communication, radar, navigation, etc. and has important research value. Since the 1970s, the direction of arrival estimation algorithm based on subspace decomposition has emerged. The orthogonality of the signal subspace and the noise subspace has greatly improved the resolution. However, this type of method requires the number of estimated sources and the method is computationally intensive, making it difficult to implement in practical applications.

[0003] In the prior art, the above problem is solved by fixing the step size. Specifically, an arrival direction estimation method based on adaptive filtering is adopted to adaptively adjust the weight of the null trap auxiliary array to form a zero value in the signal arrival direction. This type of method is based on an adaptive null trap array and estimates the direction by updating the weight of the null trap auxiliary array based on a fixed step size. It overcomes the shortcomings of the subspace decomposition-based method. However, the fixed step size cannot be adjusted accordingly according to the change of the signal-to-noise ratio in practical applications, and may even result in incorrect estimation.

[0004] In order to solve this problem, a wave direction of arrival estimation method based on updating weights with variable step size has been proposed. The method combines the cost function with the idea of ​​variable step size, makes up for the defect of performance distortion of conventional wave direction of arrival estimation method under the background of pulse noise, can adjust the weight under different signal-to-noise ratio conditions, and has good estimation performance. However, since the incident signal will generate signal noise after being incident on the adaptive null array, and the null array auxiliary array of the adaptive null array actually receives the incident signal with signal noise added when receiving the incident signal, although this method sets an adjustment factor for adjustment, the adjustment factor is the adjustment factor of the estimated azimuth spectrum, and it cannot be adjusted according to the signal noise of the incident signal received by the null array auxiliary array. That is, although the estimation result is adjusted, the actual estimation of the weight by this method is still biased, resulting in limited actual estimation accuracy. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a method and apparatus for azimuth estimation, so as to solve the problem that the estimation of weights in the prior art is actually biased, resulting in limited actual estimation accuracy.

[0006] To achieve the above-mentioned purpose and other related purposes, the present invention provides a method for estimating direction of arrival, which comprises: using an N-element adaptive nulling array to receive incident signals from multiple information sources incident from different directions; iteratively updating a nulling array weight vector in combination with a variable step size algorithm according to the incident signals from multiple information sources incident from different directions received by the N-element adaptive nulling array and a deviation compensation factor of the N-element adaptive nulling array, so as to obtain a final nulling array weight vector; and using the final nulling array weight vector to perform processing on the N-element adaptive nulling array to obtain a direction estimation result of the incident signals from multiple information sources incident to the N-element adaptive nulling array from different directions.

[0007] In one embodiment, the N-element adaptive null array includes a null array reference array and a null array auxiliary array, and the method of using the N-element adaptive null array to receive incident signals from multiple sources incident from different directions includes:

[0008] The null array reference array and the null array auxiliary array are used to receive incident signals with signal noise added thereto from multiple information sources incident from different directions.

[0009] In one embodiment, the null array weight vector is iteratively updated in combination with a variable step size algorithm according to the incident signals of several sources incident from different directions received by the N-ary adaptive null array and the deviation compensation factor of the N-ary adaptive null array to obtain the final null array weight vector, wherein the deviation compensation factor of the N-ary adaptive null array is obtained by the following method:

[0010] ,in: is the noise power of the zero-deformation reference array, is the noise power of the zero-deformation auxiliary array, is the deviation compensation factor, Compute the sign for the standard deviation.

[0011] In one embodiment, the iterative updating of the null array weight vector in combination with a variable step size algorithm based on incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array to obtain a final null array weight vector includes:

[0012] Obtaining the null sink array weight vector using the estimated weight vector step size and the deviation compensation factor;

[0013] The nulling array weight vector is iteratively updated according to incident signals from multiple information sources received by the N-element adaptive nulling array and incident from different directions, so as to obtain the final nulling array weight vector.

[0014] In one embodiment, the using the final nulling array weight vector to process on the N-tuple adaptive nulling array to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-tuple adaptive nulling array from different azimuths includes:

[0015] Obtaining a zero-stuck array auxiliary array weight vector using the final zero-stuck array weight vector;

[0016] The azimuth spectrum function and the auxiliary array weight vector of the nulling array are used to obtain the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths.

[0017] In one embodiment, the azimuth spectrum function and the null array auxiliary array weight vector are used to obtain the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive null array from different azimuths, and the azimuth estimation results are obtained by the following azimuth spectrum function:

[0018] ,in is the weight vector of the auxiliary array of the zero trap, is the result of the orientation estimation, is the steering vector of the incident signal of the source incident on the auxiliary array of the zero trap array, and H represents the conjugate transpose.

[0019] In one embodiment, in the step of obtaining the nulling array weight vector by using the estimated weight vector step length and the deviation compensation factor, the method of obtaining the estimated weight vector step length includes:

[0020] Obtaining a zero-stuck array received signal estimation error using the zero-stuck array auxiliary array received signal and the zero-stuck array reference array received signal;

[0021] The error of the received signal of the null trap array is used to obtain the auxiliary array of the null trap array. The instantaneous cumulative error at the moment;

[0022] The signal is received by the zero trap auxiliary array to obtain the zero trap auxiliary array in Estimated power at the moment;

[0023] Utilizing the zero trap auxiliary array to receive a signal and obtain a variable step size convergence upper limit;

[0024] By the variable step size convergence upper limit, the The estimated power at the time and the The instantaneous accumulated error at the time instant determines the step size of the estimated weight vector.

[0025] In one embodiment, the variable step size converges to the upper limit, the The estimated power at the time and the The instantaneous accumulated error at the time instant determines the estimated weight vector step size, including determining the estimated weight vector step size in the following manner:

[0026] ,

[0027] in: and is the correction parameter, is the upper limit of variable step size convergence, for The instantaneous cumulative error at time, is the estimated power at time k, and its value range is .

[0028] In one embodiment, in the step of using the estimated weight vector step size and the deviation compensation factor to obtain the null sinking array weight vector, the null sinking array weight vector is obtained in the following manner:

[0029] ,in: is the received signal of the zero trap auxiliary array at time 𝑘, is the weight vector of the null-steering array at time 𝑘, 𝑒(𝑘) is the received signal estimation error of the null-steering array at time 𝑘, * is represented by a conjugate matrix, 𝜇 is the estimated weight vector step size, 𝜀 is the deviation compensation factor, and H is represented by a conjugate transpose.

[0030] To achieve the above-mentioned object and other related objects, the present invention provides a device for estimating a direction of arrival, comprising:

[0031] A signal receiving module, used for receiving incident signals from multiple sources incident from different directions using an N-element adaptive null array;

[0032] A calculation module, configured to iteratively update the null array weight vector in combination with a variable step size algorithm according to incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array, so as to obtain a final null array weight vector;

[0033] The azimuth estimation module is used to use the final null array weight vector to perform processing on the N-ary adaptive null array to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-ary adaptive null array from different azimuths.

[0034] The invention is based on an adaptive null trap array, which is divided into a reference array and an auxiliary array, both of which receive incident signals. The null trap array weight vector is solved for the auxiliary array according to a minimum mean square error criterion, the weight vector is optimized by using a variable step size idea, the iterative update speed of the weight is accelerated, and the null trap array weight vector is further optimized by using a deviation compensation idea, so that it is converted from a biased estimation to an unbiased estimation, thereby improving the arrival azimuth estimation performance. Compared with the existing null trap array azimuth estimation method of the same type, the invention can not only obtain better estimation accuracy, but also has a lower RMSE under a low signal-to-noise ratio, and the invention can always maintain a low RMSE result as the signal-to-noise ratio increases. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the method for estimating the direction of arrival of the present invention;

[0036] Figure 2 The present invention is a sub-flow chart for iteratively updating the null array weight vector in combination with a variable step size algorithm according to incident signals from multiple sources incident from different directions received by the N-element adaptive null array and the deviation compensation factor of the N-element adaptive null array to obtain a final null array weight vector;

[0037] Figure 3 A sub-flow chart for calculating the estimated weight vector step length of the present invention;

[0038] Figure 4 A sub-flow chart of the present invention using the final null array weight vector to process on the N-element adaptive null array to obtain the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive null array from different azimuths;

[0039] Figure 5 is a functional module diagram of the direction of arrival estimation device of the present invention;

[0040] Figure 6 is a system block diagram of the adaptive zero trap array of the present invention;

[0041] Figure 7 It is the azimuth estimation spectrum of the present invention, method 1 and method 2 under low signal-to-noise ratio;

[0042] Figure 8 The minimum mean square error (RMSE) curves of the present invention and method 2 under different signal-to-noise ratios;

[0043] Fig. 9 The following are the successful detection probability curves of the azimuth estimation of each method under different signal-to-noise ratios for the present invention and method 2. DETAILED DESCRIPTION

[0044] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0045] See also Figure 1-9 It should be noted that the illustrations provided in this embodiment are only used to illustrate the basic concept of the present invention in a schematic manner, and the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0046] In order to solve the problem that the arrival direction estimation algorithm based on subspace decomposition needs to estimate the number of sources and the method has a large amount of calculation and is difficult to implement in practical applications, the existing technology adopts an arrival direction estimation method based on adaptive filtering, that is, method 1, which adaptively adjusts the weights of the zero trap array auxiliary array to form a zero value in the signal arrival direction. This type of method is based on an adaptive null trap array and estimates the direction by updating the weights of the zero trap array auxiliary array based on a fixed step size. It overcomes the shortcomings of the subspace decomposition-based method. However, the fixed step size cannot be adjusted accordingly according to the change of the signal-to-noise ratio in practical applications, and may even result in incorrect estimation.

[0047] In order to solve this problem, a wave direction estimation method based on updating weights with variable step size has been proposed, namely, method 2. It combines the cost function with the idea of ​​variable step size, makes up for the defect of performance distortion of conventional wave direction estimation methods under the background of pulse noise, can adjust weights under different signal-to-noise ratio conditions, and has good estimation performance. However, since the incident signal will generate signal noise after being incident on the adaptive null array, and the null array auxiliary array of the adaptive null array actually receives the incident signal with signal noise added when receiving the incident signal, although this method sets an adjustment factor for adjustment, its adjustment factor is the adjustment factor of the estimated azimuth spectrum, and it cannot be adjusted according to the signal noise of the incident signal received by the null array auxiliary array. That is, although the estimation result is adjusted, the actual estimation of the weight by this method is still biased, resulting in limited actual estimation accuracy.

[0048] Figure 1 Schematic diagram of the present invention. Figure 1 , providing a method for azimuth estimation:

[0049] S10: using an N-element adaptive null array to receive incident signals from multiple sources incident from different directions;

[0050] Before performing step S10, an N-element adaptive null array needs to be built first. The N-element adaptive null array includes a null array reference array and N-1 null array auxiliary arrays.

[0051] The incident signal from the source to the N-element adaptive null array is generally a single-frequency pulse signal, which is used as the original incident signal and is recorded as , the original incident signal After entering the N-element adaptive null array, additional signal noise will be generated. Therefore, the signals received by the null array reference array and the N-1 null array auxiliary arrays are the original incident signals with signal noise added. .

[0052] The signal receiving model is:

[0053]

[0054] Among them, the zero trap reference array and the zero trap auxiliary array both receive signals through the above model. The received signal at time , the zero trap reference array is The received signal at time , For The moment of incidence A source signal, is the number of information sources, It is The source signal is incident on the steering vector corresponding to the array. For the The incident angle of the source signal incident on the corresponding array is, is The noise vector at time ,

[0055] .

[0056] S20: According to the incident signals from multiple sources incident from different directions received by the N-ary adaptive nulling array and the deviation compensation factor of the N-ary adaptive nulling array, the nulling array weight vector is iteratively updated in combination with a variable step size algorithm to obtain a final nulling array weight vector.

[0057] See also Figure 2 , step S20 specifically includes the following steps:

[0058] S21: Obtain the nulling array weight vector using the estimated weight vector step size and the deviation compensation factor.

[0059] See also Figure 3When calculating the estimated weight vector step length in step S21, the following steps are specifically included:

[0060] S211: Obtain a null array received signal estimation error using the null array auxiliary array received signal and the null array reference array received signal.

[0061] Update and calculate the estimated error of the received signal by the zero-stuck array The formula is:

[0062]

[0063] in, The auxiliary array is zero-trapped in The received signal at the time, The reference array is zero-deep The received signal at the time, For the zero-pitched array The weight vector at time.

[0064] S212: Utilize the estimation error of the received signal of the null array to obtain the null array auxiliary array. The instantaneous accumulated error at time.

[0065] Update calculation instantaneous cumulative error The formula is:

[0066]

[0067] in, For the zero-pitched array The received signal estimation error at time , Compute the sign for the standard deviation.

[0068] S213: Utilize the null-stuck auxiliary array to receive the signal and obtain the null-stuck auxiliary array Estimated power at the moment.

[0069] Update the auxiliary array for calculating the zero trap array in Estimated power at time The formula is:

[0070]

[0071] in, The auxiliary array is zero-trapped in The received signal at the time, The reference array is zero-deep The received signal at the time, For the zero-pitched array The weight vector at time , H is expressed as the conjugate transpose.

[0072] S214: using the zero trap auxiliary array to receive the signal and obtain the variable step size convergence upper limit;

[0073] Update the calculation of variable step size convergence upper limit The formula is:

[0074]

[0075] in: is the scaling factor, which can be in the range of .

[0076] S215: Converging the upper limit through the variable step size, The estimated power at the time and the The instantaneous accumulated error at the time instant determines the step size of the estimated weight vector.

[0077] Among them, step S215 is specifically as follows:

[0078] The calculated zero trap auxiliary array is The instantaneous cumulative error at the time With the zero trap auxiliary array in Estimated power at time Combined calculation to estimate the weight vector step size , the output estimated weight vector step size Conditions that need to be met: If the calculated estimated weight vector step size , then the output estimated weight vector step length is Equal to the variable step size convergence upper limit , if the calculated estimated weight vector step size is Less than the variable step size convergence upper limit , then the output calculated estimated weight vector step length .

[0079] Update the step size of the estimated weight vector The formula is:

[0080]

[0081] in: and is a correction parameter, and its value range is .

[0082] In addition, the deviation compensation factor of the N-ary adaptive null array is related to the noise power of the null array reference array and the noise power of the null array auxiliary array of the N-ary adaptive null array. The specific calculation formula of the deviation compensation factor is:

[0083]

[0084] in, is the deviation compensation factor, is the noise power of the zero-deformation reference array, is the noise power of the null-steering auxiliary array, and N is the number of elements of the adaptive null-steering array.

[0085] In a further embodiment, the null array weight vector The formula is obtained through the cost function, and the zero-sink array weight vector is obtained through the cost function. Before formulating, you need to initialize the parameters first, and then establish The cost function at time.

[0086] The specific parameter initialization is:

[0087] set up ,initialization and ,in: is the estimated azimuth spectrum, To assist the array in receiving signals, is the zero-deflection reference array receiving signal, is the zero-sink array weight vector, is the weight vector of the auxiliary array of the zero trap, is the estimation error of the received signal with zero trapping, is the estimated weight vector step size, is the deviation compensation factor.

[0088] The cost function at the moment is:

[0089]

[0090] in, For the zero-pitched array The weight vector at time, For the zero-pitched array The received signal estimation error at time t, * represents the conjugate matrix, H represents the conjugate transpose of the matrix, Compute the sign for the standard deviation.

[0091] By calculating the cost function with respect to the null array weight vector The partial derivative is set equal to 0 to obtain the zero-sinking array weight vector The formula is:

[0092]

[0093] in, The auxiliary array is zero-trapped in The received signal at the time, For the zero-pitched array The weight vector at time, For the zero-pitched array The received signal estimation error at time , * represents the conjugate matrix, 𝜇 is the estimation weight vector step size, and 𝜀 is the deviation compensation factor.

[0094] In the zero-sinking array weight vector In the process of solving, the variable step size idea is used to obtain the required zero-sink array weight vector Optimize by using the estimated weight vector step size , speeding up the zero-sinking array weight vector The iterative update speed is 100%, and the noise power of the reference array of the zero trap array and the noise power of the auxiliary array of the zero trap array are combined as the deviation compensation factor and substituted into the weight vector of the zero trap array by using the deviation compensation idea. In the formula, the null array weight vector is further optimized to transform it from biased estimation to unbiased estimation, thereby improving the performance of azimuth-of-arrival estimation.

[0095] S22: iteratively updating the nulling array weight vector according to incident signals from multiple information sources received by the N-element adaptive nulling array and incident from different directions, so as to obtain the final nulling array weight vector.

[0096] In step S22, the null array weight vector is iteratively updated by the following iterative formula to obtain a final null array weight vector:

[0097]

[0098] in, is the estimated weight vector step size, is the estimation error of the received signal with zero trapping, To assist the array in receiving signals, is the deviation compensation factor, * represents the conjugate matrix, and H represents the conjugate transpose.

[0099] That is to complete the zero sink array weight vector After the calculation, the above formula is used for iterative calculation. Specifically: each time the calculation is performed, ,like , then the output , otherwise continue iterating until the condition is met: , and the output As the final null array weight vector, is the maximum number of iterations, the maximum number of iterations The value is the preset value.

[0100] S30: Using the final nulling array weight vector to perform processing on the N-tuple adaptive nulling array, obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-tuple adaptive nulling array from different azimuths.

[0101] See also Figure 4 , step S30 specifically includes:

[0102] S31: Calculate the auxiliary null array weight vector using the final null array weight vector.

[0103] Zero trap auxiliary array weight vector The calculation formula is:

[0104]

[0105] in is the final null sink array weight vector obtained.

[0106] S32: Calculate the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths using the azimuth spectrum function and the nulling array auxiliary array weight vector.

[0107] Among them, the azimuth spectrum function is expressed as:

[0108]

[0109] in is the weight vector of the auxiliary array of the zero trap, H represents the conjugate transpose, is the result of the orientation estimation, is the steering vector of the incident signal from the source incident on the auxiliary array of the zero trap array.

[0110] in, Figure 5 is a system block diagram of the adaptive nulling array of this embodiment.

[0111] Simulation conditions:

[0112] Three single-frequency pulse signals are used as incident signal sources, which are incident on a 10-element adaptive null array from different directions. The number of snapshots (the number of sampling points of the entire array in the time domain) is 200, and the sensor array is arranged at half the wavelength. Method 1, method 2 and the method of this embodiment are compared and analyzed.

[0113] Figure 6 azimuth estimation spectra of this embodiment, method 1 and method 2 under low signal-to-noise ratio;

[0114] The design azimuths are 0°, 30° and 35°, respectively, and the signal-to-noise ratio is 0dB. By comparison, it can be seen that method 1 cannot accurately estimate the azimuth under low signal-to-noise ratio, and even has the phenomenon of misestimation. Although method 2 can estimate the target azimuth, it cannot accurately distinguish two close targets. This embodiment can accurately judge the angles of the three azimuths according to the peak position of the azimuth spectrum, and the estimation accuracy is stronger than method 1 and method 2.

[0115] Figure 7 RMSE curves of this embodiment and method 2 under different signal-to-noise ratios;

[0116] It can be found that the RMSE of this embodiment is lower and the accuracy is higher under low signal-to-noise ratio. As the signal-to-noise ratio increases, the method of this embodiment can always maintain a low RMSE result.

[0117] Figure 8 The successful detection probability curves of the azimuth estimation of each method under different signal-to-noise ratios for this embodiment and method 2;

[0118] It can be found that the success detection probability of this embodiment is more accurate, and also has a higher success probability under a low signal-to-noise ratio, and has stronger stability.

[0119] See also Figure 4 , a wave arrival direction estimation device is provided, including: a signal receiving module 10, a calculation module 20 and a direction estimation module 30.

[0120] The signal receiving module 10 is used to receive incident signals from multiple sources incident from different directions using an N-element adaptive null array.

[0121] The calculation module 20 is used to iteratively update the null array weight vector in combination with a variable step size algorithm according to the incident signals from multiple sources received by the N-ary adaptive null array and incident from different directions and the deviation compensation factor of the N-ary adaptive null array, so as to obtain a final null array weight vector.

[0122] The azimuth estimation module 30 is used to use the final nulling array weight vector to perform processing on the N-ary adaptive nulling array to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-ary adaptive nulling array from different azimuths.

[0123] It should be noted that the direction of arrival estimation device of the present invention is a virtual device corresponding to the above-mentioned direction of arrival estimation method, and the functional modules in the direction of arrival estimation device respectively correspond to the corresponding steps in the direction of arrival estimation method. The direction of arrival estimation device of the present invention can be implemented in conjunction with the direction of arrival estimation method. The relevant technical details mentioned in the direction of arrival estimation method of the present invention are still valid in the direction of arrival estimation device, and will not be repeated here to reduce repetition. Accordingly, the relevant technical details mentioned in the direction of arrival estimation device of the present invention can also be applied to the above-mentioned medical image report annotation model training method.

[0124] It should be noted that the above-mentioned functional modules can be fully or partially integrated into one physical entity during actual implementation, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, some or all of the steps of the above method, or the above functional modules can be completed by hardware integrated logic circuits in the processor element or instructions in software form.

[0125] In the description herein, many specific details, such as examples of components and / or methods, are provided to provide a complete understanding of embodiments of the present invention. However, those skilled in the art will recognize that embodiments of the present invention may be practiced without one or more of the specific details or with other devices, systems, components, methods, components, materials, parts, etc. In other cases, well-known structures, materials, or operations are not specifically shown or described in detail to avoid obscuring aspects of embodiments of the present invention.

[0126] References throughout the specification to "one embodiment," "an embodiment," or "a specific embodiment" mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention, and not necessarily in all embodiments. Thus, various appearances of the phrases "in one embodiment," "in an embodiment," or "in a specific embodiment" in different places throughout the specification do not necessarily refer to the same embodiment. In addition, the particular features, structures, or characteristics of any specific embodiment of the invention may be combined with one or more other embodiments in any suitable manner. It should be understood that other variations and modifications of the embodiments of the invention described and illustrated herein may be possible in light of the teachings herein and are to be considered part of the spirit and scope of the invention.

[0127] It should also be understood that one or more of the elements shown in the figures may also be implemented in a more separate or more integrated manner, or even removed because they are inoperable in certain circumstances or provided because they may be useful depending on the application.

[0128] In addition, unless otherwise explicitly indicated, any marking arrows in the drawings should be regarded as exemplary only and not limiting. In addition, unless otherwise indicated, the term "or" used herein is generally intended to mean "and / or". In the case where the term is not clear because it is anticipated that the ability to separate or combine is provided, the combination of components or steps will also be regarded as indicated.

[0129] As used in the description herein and throughout the claims that follow, “a,” “an,” and “the” include plural references unless otherwise indicated. Likewise, as used in the description herein and throughout the claims that follow, the meaning of “in” includes “in” and “on,” unless otherwise indicated.

[0130] The above description of the illustrated embodiments of the present invention (including the contents described in the Abstract) is not intended to be an exhaustive list or to limit the present invention to the precise form disclosed herein. Although specific embodiments of the present invention and examples of the present invention are described herein for illustrative purposes only, various equivalent modifications are possible within the spirit and scope of the present invention as will be recognized and appreciated by those skilled in the art. As noted, these modifications may be made to the present invention in accordance with the above description of the embodiments described in the present invention, and these modifications will be within the spirit and scope of the present invention.

[0131] Systems and methods have been generally described herein as details that aid in understanding the present invention. In addition, various specific details have been given to provide an overall understanding of embodiments of the present invention. However, those skilled in the relevant art will recognize that embodiments of the present invention may be practiced without one or more of the specific details, or may be practiced using other devices, systems, accessories, methods, components, materials, parts, etc. In other cases, well-known structures, materials, and / or operations are not specifically shown or described in detail to avoid confusion with various aspects of embodiments of the present invention.

[0132] Thus, although the invention has been described herein with reference to specific embodiments thereof, freedom of modification, various changes and substitutions are intended within the foregoing disclosure, and it should be understood that in some cases, some features of the invention will be employed without the corresponding use of other features without departing from the scope and spirit of the proposed invention. Thus, many modifications may be made to adapt a particular environment or material to the essential scope and spirit of the invention. The invention is not intended to be limited to the specific terms used in the claims below and / or the specific embodiments disclosed as the best mode contemplated for carrying out the invention, but the invention will include any and all embodiments and equivalents falling within the scope of the appended claims. Thus, the scope of the invention will be determined solely by the appended claims.

Claims

1. A method for estimating a direction of arrival, characterized in that: The azimuth-of-arrival estimation method comprises: An N-element adaptive null array is used to receive incident signals from a plurality of sources incident from different directions; Iteratively updating the null array weight vector in combination with a variable step size algorithm according to incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array, so as to obtain a final null array weight vector; Processing the N-element adaptive nulling array using the final nulling array weight vector to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths; The method of iteratively updating the null array weight vector in combination with a variable step size algorithm based on incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array to obtain a final null array weight vector includes: Obtaining the null sink array weight vector using the estimated weight vector step size and the deviation compensation factor; The nulling array weight vector is iteratively updated according to incident signals from multiple information sources received by the N-element adaptive nulling array and incident from different directions, so as to obtain the final nulling array weight vector.

2. The method for estimating the direction of arrival according to claim 1, characterized in that: The N-element adaptive null array includes a null array reference array and a null array auxiliary array, and the method of using the N-element adaptive null array to receive incident signals from multiple sources incident from different directions includes: The null array reference array and the null array auxiliary array are used to receive incident signals with signal noise added thereto from multiple information sources incident from different directions.

3. The method for estimating the direction of arrival according to claim 2, wherein: According to the incident signals received by the N-ary adaptive null array from multiple sources incident from different directions and the deviation compensation factor of the N-ary adaptive null array, the null array weight vector is iteratively updated in combination with a variable step size algorithm to obtain a final null array weight vector, wherein the deviation compensation factor of the N-ary adaptive null array is obtained by the following method: ,in: is the noise power of the zero-deformation reference array, is the noise power of the zero-deformation auxiliary array, is the deviation compensation factor, Compute the sign for the standard deviation.

4. The method for estimating the direction of arrival according to claim 1, wherein: The method of using the final nulling array weight vector to process the N-element adaptive nulling array to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths includes: Obtaining a zero-stuck array auxiliary array weight vector using the final zero-stuck array weight vector; The azimuth spectrum function and the auxiliary array weight vector of the nulling array are used to obtain the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths.

5. The method for estimating the direction of arrival according to claim 4, characterized in that: The azimuth spectrum function and the nulling array auxiliary array weight vector are used to obtain the azimuth estimation results of the incident signals of the plurality of information sources incident on the N-element adaptive nulling array from different azimuths, and the azimuth estimation results are obtained by the following azimuth spectrum function: ,in is the weight vector of the auxiliary array of the zero trap, is the result of the orientation estimation, is the steering vector of the incident signal of the source incident on the auxiliary array of the zero trap array, and H represents the conjugate transpose.

6. The method for estimating direction of arrival according to claim 1, characterized in that: In the step of obtaining the nulling array weight vector by using the estimated weight vector step length and the deviation compensation factor, the method of obtaining the estimated weight vector step length includes: Obtaining a zero-stuck array received signal estimation error using the zero-stuck array auxiliary array received signal and the zero-stuck array reference array received signal; The error of the received signal of the null trap array is used to obtain the auxiliary array of the null trap array. The instantaneous cumulative error at the moment; The signal is received by the zero trap auxiliary array to obtain the zero trap auxiliary array in Estimated power at the moment; Utilizing the zero trap auxiliary array to receive a signal and obtain a variable step size convergence upper limit; By the variable step size convergence upper limit, the The estimated power at the time and the The instantaneous accumulated error at the time instant determines the step size of the estimated weight vector.

7. The method for estimating the direction of arrival according to claim 6, characterized in that: The variable step size converges to the upper limit, the The estimated power at the time and the The instantaneous accumulated error at the time instant determines the estimated weight vector step size, including determining the estimated weight vector step size in the following manner: ， in: and is the correction parameter, is the upper limit of variable step size convergence, for The instantaneous cumulative error at time, is the estimated power at time k, and its value range is .

8. The method for estimating direction of arrival according to claim 1, wherein: In the step of obtaining the null sink array weight vector by using the estimated weight vector step size and the deviation compensation factor, the null sink array weight vector is obtained by: ,in: is the received signal of the zero trap auxiliary array at time 𝑘, is the weight vector of the null-steering array at time 𝑘, 𝑒(𝑘) is the received signal estimation error of the null-steering array at time 𝑘, * is represented by a conjugate matrix, 𝜇 is the estimated weight vector step size, 𝜀 is the deviation compensation factor, and H is represented by a conjugate transpose.

9. A direction of arrival estimation device, characterized in that: include: A signal receiving module, used for receiving incident signals from multiple sources incident from different directions using an N-element adaptive null array; A calculation module, configured to iteratively update the null array weight vector in combination with a variable step size algorithm according to incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array, so as to obtain a final null array weight vector; an azimuth estimation module, configured to use the final null array weight vector to perform processing on the N-element adaptive null array to obtain azimuth estimation results of incident signals of the plurality of information sources incident on the N-element adaptive null array from different azimuths; The method of iteratively updating the null array weight vector in combination with a variable step size algorithm based on incident signals from multiple sources received by the N-element adaptive null array and incident from different directions and a deviation compensation factor of the N-element adaptive null array to obtain a final null array weight vector includes: Obtaining the null sink array weight vector using the estimated weight vector step size and the deviation compensation factor; The nulling array weight vector is iteratively updated according to incident signals from multiple information sources received by the N-element adaptive nulling array and incident from different directions, so as to obtain the final nulling array weight vector.

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