Source number estimation method and device, direction of arrival estimation method, radar system and vehicle

Abstract

The embodiment of the invention provides an information source number estimation method and device, a direction of arrival estimation method, a radar system and a vehicle. The information source number estimation method comprises the following steps: acquiring an array signal of a radar; determining a target amplitude error sum-of-squares threshold value corresponding to the signal source number based on a first mapping relation corresponding to the signal source number and a target signal-to-noise ratio of the array signal; the mapping relation comprises a first mapping relation between the signal source signal-to-noise ratio and the amplitude error square sum threshold value; and estimating the signal source number corresponding to the array signal according to the amplitude error quadratic sum of the array signal and a target amplitude error quadratic sum threshold value corresponding to the signal source number. Through the signal-to-noise ratio of the array signal, the self-adaptive first amplitude error sum-of-squares threshold is determined, the amplitude error sum-of-squares of the array signal is judged, the signal source number of the array signal is estimated, the influence of the signal-to-noise ratio is small, the signal source number is estimated through the amplitude error sum-of-squares, and calculation is simple.

Description

Technical Field

[0001] The present application relates to the technical field of signal processing, and in particular, to a method and device for estimating the number of signal sources, a method for estimating the direction of arrival, a radar system, and a vehicle. Background Art

[0002] Millimeter-wave radar plays a crucial role in intelligent driving. It provides accurate distance, speed, and angle data, has strong anti-interference capabilities, and supports advanced intelligent driving functions. However, the actual environment detected by millimeter-wave radar is relatively complex, and there are targets at different angles with the same distance and speed, which poses higher requirements for the angle resolution performance of millimeter-wave radar. To achieve higher angle resolution performance, sparse MIMO arrays and super-resolution algorithms are usually used for angle measurement. To reduce false alarms and save computing resources, different angle measurement algorithms are usually set for different numbers of signal sources. Therefore, correctly judging the number of signal sources is the key to accurately resolving angles at the same distance and speed. Overestimating or underestimating the number of signal sources will affect the angle measurement result. Therefore, how to judge the number of signal sources is crucial.

[0003] Existing methods for estimating the number of signal sources usually use the covariance matrix to estimate the number of signal sources. When calculating the covariance matrix and solving the number of signal sources through the covariance matrix, it is easily affected by signal-to-noise ratio, signal strength, array error, etc. Moreover, the calculation of the matrix is complex, which will greatly affect the accuracy of the estimated result of the number of signal sources. Summary of the Invention

[0004] Embodiments of the present application provide a method and device for estimating the number of signal sources, a method for estimating the direction of arrival, a radar system, and a vehicle, so as to reduce the influence of signal-to-noise ratio on the estimated result of the number of signal sources.

[0005] In a first aspect, embodiments of the present application provide a method for estimating the number of signal sources, the method including:

[0006] Obtain the array signal of the radar;

[0007] Based on a first mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal, determine a target mean squared amplitude error threshold corresponding to the number of signal sources; the first mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean squared amplitude error threshold;

[0008] Estimate the number of signal sources corresponding to the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources.

[0009] In a possible implementation manner, the first mapping relationship corresponding to the number of signal sources includes a first sub-mapping relationship corresponding to the number of signal sources being 1; the target mean squared amplitude error threshold corresponding to the number of signal sources includes: a first mean squared amplitude error threshold corresponding to the number of signal sources being 1;

[0010] Estimate the number of signal sources corresponding to the array signal according to the sum of squared amplitude errors of the array signal and the target sum of squared amplitude error threshold corresponding to the number of signal sources, including:

[0011] When the sum of squared amplitude errors of the array signal is less than or equal to the first sum of squared amplitude error threshold, determine that the number of signal sources of the array signal is 1;

[0012] When the sum of squared amplitude errors of the array signal is greater than the first sum of squared amplitude error threshold, determine that the number of signal sources of the array signal is greater than 1.

[0013] In a possible implementation manner, the first mapping relationship corresponding to the number of signal sources includes a second sub-mapping relationship corresponding to the number of signal sources being 2; the target sum of squared amplitude error threshold corresponding to the number of signal sources includes: the second sum of squared amplitude error threshold corresponding to the number of signal sources being 2;

[0014] Estimate the number of signal sources corresponding to the array signal according to the sum of squared amplitude errors of the array signal and the target sum of squared amplitude error threshold corresponding to the number of signal sources, including:

[0015] When the sum of squared amplitude errors of the array signal is greater than the first sum of squared amplitude error threshold, estimate the number of signal sources corresponding to the array signal according to the second sum of squared amplitude error threshold of the array signal.

[0016] In a possible implementation manner, estimating the number of signal sources corresponding to the array signal according to the second sum of squared amplitude error threshold of the array signal includes:

[0017] Based on the second mapping relationship corresponding to the number of signal sources and the second sum of squared amplitude error threshold, determine the target conditional probability corresponding to the number of signal sources; the second mapping relationship includes: the mapping relationship between the second sum of squared amplitude error threshold and the conditional probability;

[0018] Estimate the number of signal sources corresponding to the array signal according to the target conditional probability corresponding to the number of signal sources.

[0019] In a possible implementation manner, the second mapping relationship corresponding to the number of signal sources includes a third sub-mapping relationship corresponding to the number of signal sources being 2; the target conditional probability corresponding to the number of signal sources includes: the first conditional probability of the number of signal sources being 2; estimating the number of signal sources corresponding to the array signal according to the target conditional probability corresponding to the number of signal sources includes:

[0020] According to the first conditional probability corresponding to the array signal, determine the first posterior probability that the number of signal sources of the array signal is 2;

[0021] Based on the first posterior probability that the number of signal sources of the array signal is 2, determine the estimation result of the number of signal sources of the array signal.

[0022] In a possible implementation, the second mapping relationship corresponding to the number of signal sources includes a fourth sub-mapping relationship corresponding to the number of signal sources being greater than or equal to 3; the target conditional probability corresponding to the number of signal sources includes: a second conditional probability that the number of signal sources is greater than or equal to 3.

[0023] Determining an estimated result of the number of signal sources of the array signal based on the first posterior probability that the number of signal sources of the array signal is 2 includes:

[0024] Determining a second posterior probability that the number of signal sources of the array signal is greater than or equal to 3 according to the second conditional probability corresponding to the array signal;

[0025] Taking the number of signal sources corresponding to the larger value of the first posterior probability and the second posterior probability as the estimated result of the number of signal sources of the array signal.

[0026] In a possible implementation, the first mapping relationship and the second mapping relationship corresponding to the number of signal sources are constructed based on at least part of the simulation data in the simulation data set obtained by simulation under the number of signal sources; the simulation data set includes: the sum of squared amplitude errors simulation data obtained by simulating a sample radar at different signal-to-noise ratios under the number of signal sources, and the corresponding signal-to-noise ratios.

[0027] In a possible implementation, the simulation data set includes multiple sum-of-squared amplitude error simulation values corresponding to different signal-to-noise ratios, and at least part of the simulation data includes at least one sum-of-squared amplitude error simulation value corresponding to each signal-to-noise ratio among different signal-to-noise ratios;

[0028] The at least one sum-of-squared amplitude error simulation value corresponding to the signal-to-noise ratio includes: the sum-of-squared amplitude error simulation value at the first preset position after sorting the multiple sum-of-squared amplitude error simulation values corresponding to the signal-to-noise ratio according to the first preset rule.

[0029] In a possible implementation, the first preset position is determined based on the number of experimental times of the simulation experiment and the false alarm probability.

[0030] In a possible implementation, the first mapping relationship and the second mapping relationship corresponding to the number of signal sources are function expressions obtained by fitting based on at least part of the simulation data in the simulation data set obtained by simulation under the number of signal sources.

[0031] In a possible implementation, the different signal-to-noise ratios included in the simulation data set form an arithmetic progression.

[0032] In a possible implementation, the radar is a sparse array.

[0033] In a possible implementation, the array signal of the radar is a single snapshot signal.

[0034] Second aspect, an embodiment of the present application provides a method for estimating the direction of arrival, the method comprising:

[0035] Obtain the array signal of the radar;

[0036] Based on the mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal, determine the target mean squared amplitude error threshold corresponding to the number of signal sources; the mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean squared amplitude error threshold;

[0037] Estimate the number of signal sources corresponding to the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources;

[0038] Perform direction-of-arrival estimation of the signal according to the estimation result of the number of signal sources of the array signal.

[0039] Third aspect, an embodiment of the present application provides a device for estimating the number of signal sources, the device comprising:

[0040] An acquisition module, configured to obtain the array signal of the radar;

[0041] A determination module, configured to determine the target mean squared amplitude error threshold corresponding to the number of signal sources based on the mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal; the mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean squared amplitude error threshold;

[0042] An estimation module, configured to estimate the number of signal sources of the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources.

[0043] Fourth aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementation manners of the first aspect.

[0044] Fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the above first aspect and / or various possible implementation manners of the first aspect.

[0045] Sixth aspect, an embodiment of the present application provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, it implements the above first aspect and / or various possible implementation manners of the first aspect.

[0046] Seventh aspect, an embodiment of the present application provides a radar system, which includes a signal transmitter, an array antenna, and a signal processor; the signal transmitter is used to transmit signals, and the array antenna is used to receive signals;

[0047] The signal processor is used to construct an array signal based on the received signal and estimate the number of signal sources of the array signal, specifically used to execute the above first aspect and / or various possible implementation manners of the first aspect, and the implementation manner of the second aspect.

[0048] Eighth aspect, an embodiment of the present application provides a vehicle, which includes the above radar system.

[0049] The method, device, direction-of-arrival estimation method, radar system and vehicle for estimating the number of signal sources provided by the embodiments of the present application, the method for estimating the number of signal sources includes: obtaining the array signal of the radar; determining the target mean square error threshold corresponding to the number of signal sources based on the first mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal; the first mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean square error threshold; estimating the number of signal sources corresponding to the array signal according to the mean square error of the array signal and the target mean square error threshold corresponding to the number of signal sources. By determining an adaptive first mean square error threshold through the signal-to-noise ratio of the array signal and judging the mean square error of the array signal, the number of signal sources of the array signal is estimated, which is less affected by the signal-to-noise ratio, and the number of signal sources is estimated by the mean square error, and the calculation is simple. Description of the Drawings

[0050] The drawings here are incorporated into the description and form a part of this description, showing embodiments consistent with the present application, and are used together with the description to explain the principles of the present application.

[0051] Figure 1 It is a schematic diagram of the scenario of the method for estimating the number of signal sources provided in an embodiment;

[0052] Figure 2 It is a schematic flowchart of the method for estimating the number of signal sources provided in an embodiment Figure 1 ;

[0053] Figure 3 It is a schematic structural diagram of the radar system provided in an embodiment;

[0054] Figure 4 It is a schematic flowchart of the method for estimating the number of signal sources provided in an embodiment Figure 2 ;

[0055] Figure 5 It is a schematic flowchart of the method for estimating the number of signal sources provided in an embodiment Figure 3 ;

[0056] FIG. 6(a) is a schematic diagram of a fitting curve between the first sum of squared amplitude errors threshold and SNR provided in one embodiment;

[0057] FIG. 6(b) is a schematic diagram of the success rate curve of source estimation when the number of sources is 1 provided in one embodiment;

[0058] FIG. 7(a) is a schematic diagram of the probability curve of passing the first sum of squared amplitude errors threshold when the number of sources is 2 provided in one embodiment;

[0059] FIG. 7(b) is a schematic diagram of a fitting curve between the second sum of squared amplitude errors threshold and SNR provided in one embodiment;

[0060] FIG. 7(c) is a schematic diagram of the success rate curve of source estimation when the number of sources is 2 provided in one embodiment;

[0061] FIG. 8(a) is a schematic diagram of the probability curve of passing the first sum of squared amplitude errors threshold when the number of sources is greater than or equal to 3 provided in one embodiment;

[0062] FIG. 8(b) is a schematic diagram of the success rate curve of estimation when the number of sources is greater than or equal to 3 provided in one embodiment;

[0063] Figure 9 FIG. is a schematic diagram of the flow of a direction-of-arrival estimation method provided in one embodiment;

[0064] Figure 10 FIG. is a schematic diagram of the structure of a source number estimation device provided in the present application;

[0065] Figure 11 FIG. is a schematic diagram of the structure of an electronic device provided in the present application.

[0066] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of Specific Embodiments

[0067] Here, exemplary embodiments will be described in detail, and examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0068] In the description of this application, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of this application, "a plurality of" means two or more unless otherwise specifically defined.

[0069] First, the nouns appearing in this article are explained as follows:

[0070] Millimeter-wave radar plays a crucial role in intelligent driving. It provides accurate distance, speed, and angle data, has strong anti-interference capabilities, and supports advanced intelligent driving functions. However, the actual environment detected by millimeter-wave radar is relatively complex, with targets at different angles at the same distance and speed, which poses higher requirements for the angle resolution performance of millimeter-wave radar. To achieve higher angle resolution performance, sparse MIMO (Multiple Input Multiple Output) arrays and super-resolution algorithms are usually used for angle measurement. To reduce false alarms and save computing resources, different angle measurement algorithms are usually set for different numbers of signal sources. Therefore, correctly judging the number of signal sources is the key to accurately resolving angles at the same distance and speed. Overestimating or underestimating the number of signal sources will affect the angle measurement result. Therefore, how to judge the number of signal sources is crucial.

[0071] Existing methods for estimating the number of signal sources usually use the covariance matrix to estimate the number of signal sources. When calculating the covariance matrix and solving the number of signal sources through the covariance matrix, it is easily affected by factors such as signal-to-noise ratio, signal strength, and array error. Moreover, the calculation of the matrix is complex, which will greatly affect the accuracy of the estimated result of the number of signal sources.

[0072] To address the above technical problems, the embodiments of this application provide a method for estimating the number of signal sources, which can be applied to the scenario of estimating the number of signal sources after real-time data acquisition or the scenario of estimating the number of signal sources after data acquisition. The embodiments of this application do not make specific limitations in this regard. For ease of understanding, the embodiments of this application take the application to the scenario of real-time data acquisition and estimating the number of signal sources as an example. Through the method provided by the embodiments of this application, the number of detected targets can be estimated.

[0073] The method provided by the embodiments of this application can be applied to, for example Figure 1In the application environment shown. Among them, the acquisition device 102 is used to collect the echo signal reflected by the detection target in real time. The acquisition device 102 communicates with the signal processing unit 104 through a network, sends the collected echo signal to the signal processing unit 104, and the signal processing unit 104 processes and analyzes the echo signal to realize the estimation of the number of signal sources. The data storage system can store the data that the signal processing unit 104 needs to process. The data storage system can be integrated on the signal processing unit 104, or can be placed on the cloud or other network servers.

[0074] In one embodiment, as Figure 2 shown, a method for estimating the number of signal sources is provided. Taking the application of this method to Figure 1 the signal processing unit 104 in as an example for illustration, the method includes the following steps:

[0075] Step 202, obtain the array signal of the radar;

[0076] Step 204, based on the first mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal, determine the target sum of squared amplitude errors threshold corresponding to the number of signal sources; The first mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the threshold of the sum of squared amplitude errors;

[0077] Step 206, estimate the number of signal sources of the array signal according to the sum of squared amplitude errors of the array signal and the target sum of squared amplitude errors threshold corresponding to the number of signal sources.

[0078] A plurality of sensors or receivers are arranged at different positions in space to form an array. By receiving the spatial signal field through this array, the array signal can be obtained. More accurate and reliable information can be obtained by simultaneously receiving and processing the array signal. In a radar system, a plurality of identical single antennas (such as symmetric antennas) are arranged according to a certain rule to form an array antenna, also called an antenna array. The independent units that make up the array antenna become array elements or antenna units (in the embodiments of the present application, the array elements are used as examples for illustration), and the array signal is obtained through the array antenna.

[0079] According to the arrangement rule of the array elements, the array antenna can be divided into a uniform array and a sparse array. It can be understood that a uniform array refers to an array antenna in which the spacing between any two adjacent array elements is equal and the amplitude patterns of all array elements are the same. A sparse array refers to an antenna array design in which the number of array elements is reduced according to a certain rule. The array signal in the embodiments of the present application is obtained through the array antenna in the radar system, and the structure of the array antenna is not specifically limited. However, in a specific embodiment, when the radar is a millimeter-wave radar, the array antenna is a sparse array.

[0080] The array signal of the radar in step 202 can be the original array signal obtained by the array antenna without any processing, that is, the array signal is directly constructed from the received signals of each element; the array signal of the radar can also be the array signal constructed after processing the received signals of each element, such as filtering, denoising, and gain control. In use, the array antenna is usually arranged at a fixed position to detect detection targets within the detection range. After each element in the array antenna receives a signal, the received signal is sent to the signal processing unit through the corresponding channel. After receiving the received signals of all elements, the signal processing unit needs to process the received signals of all elements to obtain the mathematical model of the array signal corresponding to the array antenna, and then perform analysis.

[0081] Exemplarily, the system structure for estimating the number of signal sources of a radar system is as Figure 3 shown. Among them, the target space 301 is the space that the array antenna can detect. The detection target reflects the transmitted signal, which is received by the array antenna. Therefore, for the array antenna, each detection target in the target space can be regarded as a signal source. Each channel in the observation space 302 corresponds to an element. After each element obtains the received signal, the received signal is sent to the processor 3031 in the estimation space 303, and the processor 3031 processes the received signal to estimate the number of signal sources. The processor 3031 will first process the received signals of all elements to obtain the array signal, and then execute the method steps provided in this embodiment to estimate the number of signal sources of the array signal. For example, the processor 3031 includes an adaptive array processor, and the signals received by each element enter the adaptive array processor for weighted summation to obtain the array signal.

[0082] The sum of the squared amplitude errors of the array signal refers to the sum of the squared amplitude errors between all the received signals that make up the array signal, representing the amplitude errors between all the received signals at the same moment. Therefore, the array signal in the embodiments of the present application usually refers to a single snapshot signal.

[0083] For a single snapshot array signal, assuming the virtual received steering vector of the signal is , the received signal is:

[0084] ,

[0085] where is the number of signal sources, is the th signal source. When the influence of the noise is small, a single signal source generates an approximately constant amplitude at each element. Therefore, the sum of the squared amplitude errors at the element level of the single snapshot echo data can be used as a suitable criterion to determine the number of signal sources. The expression of the sum of the squared amplitude errors at the element level is:

[0086] ;

[0087] Wherein, is the number of array elements in the array antenna of the radar, represents the th amplitude of the received signal of the array element, represents the mean value of the amplitudes of the received signals of all array elements.

[0088] The signal-to-noise ratio (SNR) of the array signal is used to measure the strength of the signal relative to the background noise. The calculation of SNR is usually based on the ratio of signal power to noise power, and this ratio is usually expressed in decibels (dB). In a radar system, the array signal is usually received and combined by multiple array antennas. Therefore, the signal power can be obtained by measuring the strength of the combined signal. In actual operation, techniques such as pulse compression may be required to improve the signal-to-noise ratio of the signal and accurately measure the signal power. The noise power is usually measured in the absence of a signal. In a radar system, this can be achieved by sampling in a short period of time before or after the transmitted pulse. To ensure the accuracy of the measurement, regions without signals are usually selected for noise measurement, and the average value of multiple measurements may be used to reduce random errors.

[0089] It should be noted that since the noise in the radar system may be non-stationary (i.e., its statistical characteristics may change over time), in practical applications, the signal-to-noise ratio needs to be calculated for array signals without single snapshots. Specifically, more complex noise modeling and estimation methods may be required to improve the accuracy of SNR calculation.

[0090] The first mapping relationship corresponding to the number of signal sources is used to describe the corresponding relationship between the signal-to-noise ratio of the array signal and the threshold of the sum of squared amplitude errors when the array signal is judged to be the number of signal sources. In actual application scenarios, according to the possibility of the number of signal sources to be judged, the corresponding first mapping relationship is obtained. For example, if it is necessary to judge whether the number of signal sources is 1 or greater than 1, the first sub-mapping relationship corresponding to the number of signal sources being 1 needs to be obtained; if it is necessary to judge that the number of signal sources is 2 or greater than 2, the first sub-mapping relationship corresponding to the number of signal sources being 1 and the second sub-mapping relationship corresponding to the number of signal sources being 2 need to be obtained. First, judge whether the number of signal sources is 1 according to the first sub-mapping relationship corresponding to the number of signal sources being 1. If it is not 1, then judge whether the number of signal sources is 2 according to the second sub-mapping relationship corresponding to the number of signal sources being 2.

[0091] The first mapping relationship corresponding to the number of signal sources includes, but is not limited to, the following forms: function expression, look-up table, and prediction model. Among them, the function expression is a linear relationship. By substituting the signal-to-noise ratio of the array signal into the function expression, the target mean squared amplitude error threshold corresponding to the number of signal sources can be directly obtained. The look-up table is discrete. When determining the target mean squared amplitude error threshold corresponding to the number of signal sources, if the target mean squared amplitude error threshold corresponding to the signal-to-noise ratio of the array signal cannot be found in the look-up table, then the corresponding target mean squared amplitude error threshold can be determined by means of linear interpolation using the reference signal-to-noise ratio adjacent to the signal-to-noise ratio of the array signal. For the prediction model, directly input the signal-to-noise ratio of the array signal into the corresponding trained model for the number of signal sources, and the corresponding target mean squared amplitude error threshold can be obtained.

[0092] Specifically, through the first mapping relationship corresponding to the number of signal sources and the signal-to-noise ratio of the array signal, determine the target mean squared amplitude error threshold corresponding to the number of signal sources when the array signal has this signal-to-noise ratio. Then, compare the mean squared amplitude error of the array signal with the target mean squared amplitude error threshold corresponding to the number of signal sources, and determine whether the mean squared amplitude error of the array signal satisfies the characteristics of the mean squared amplitude error at this number of signal sources, so as to determine whether the number of signal sources of the array signal is this number of signal sources.

[0093] In the method provided in the above embodiment, obtain the array signal of the radar; based on the first mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal, determine the target mean squared amplitude error threshold corresponding to the number of signal sources; the first mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean squared amplitude error threshold; estimate the number of signal sources corresponding to the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources. By means of the signal-to-noise ratio of the array signal, determine the adaptive first mean squared amplitude error threshold, and judge the mean squared amplitude error of the array signal, so as to estimate the number of signal sources of the array signal. It is less affected by the signal-to-noise ratio, and the number of signal sources is estimated by means of the mean squared amplitude error, and the calculation is simple.

[0094] In one embodiment, the first mapping relationship corresponding to the number of signal sources includes the first sub-mapping relationship corresponding to the number of signal sources being 1; the target mean squared amplitude error threshold corresponding to the number of signal sources includes: the first mean squared amplitude error threshold corresponding to the number of signal sources being 1;

[0095] Estimating the number of signal sources corresponding to the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources includes:

[0096] When the mean squared amplitude error of the array signal is less than or equal to the first mean squared amplitude error threshold, determine that the number of signal sources of the array signal is 1;

[0097] When the sum of squares of amplitude errors of the array signal is greater than the first sum-of-squares-of-amplitude-errors threshold, it is determined that the number of signal sources of the array signal is greater than 1.

[0098] The first sub-mapping relationship corresponding to the number of signal sources being 1 refers to the first mapping relationship between the sum-of-squares-of-amplitude-errors threshold and the signal-to-noise ratio determined in the scenario where the number of signal sources is 1, which can be determined by the historical operation data or simulation operation data of the radar in the scenario where the number of signal sources is 1. Correspondingly, the target sum-of-squares-of-amplitude-errors threshold corresponding to different signal-to-noise ratios can be determined according to the first sub-mapping relationship corresponding to the number of signal sources being 1.

[0099] It is known that in a radar system, when the influence of noise is small, a single signal source generates an approximately constant amplitude at each array element. Therefore, for the scenario where the number of signal sources is 1, a first sum-of-squares-of-amplitude-errors threshold is set to judge the sum of squares of amplitude errors of the array signal to determine whether the number of signal sources of the array signal is 1. And according to the definition of the sum of squares of amplitude errors, the sum of squares of amplitude errors of the same signal source at different signal-to-noise ratios will be different. Therefore, based on the signal-to-noise ratio of the array signal, in the first sub-mapping relationship corresponding to the number of signal sources being 1, the first sum-of-squares-of-amplitude-errors threshold for judging whether the number of signal sources of the array signal is 1 is determined.

[0100] In the method provided in the above embodiment, by directly comparing the average sum of amplitude errors of the array signal with the first sum-of-squares-of-amplitude-errors threshold, it can be quickly judged whether the number of signal sources is 1.

[0101] In one of the embodiments, the first mapping relationship corresponding to the number of signal sources includes the second sub-mapping relationship corresponding to the number of signal sources being 2; the target sum-of-squares-of-amplitude-errors threshold corresponding to the number of signal sources includes: the second sum-of-squares-of-amplitude-errors threshold corresponding to the number of signal sources being 2;

[0102] Estimating the number of signal sources corresponding to the array signal according to the sum of squares of amplitude errors of the array signal and the target sum-of-squares-of-amplitude-errors threshold corresponding to the number of signal sources includes:

[0103] When the sum of squares of amplitude errors of the array signal is greater than the first sum-of-squares-of-amplitude-errors threshold, estimating the number of signal sources corresponding to the array signal according to the second sum-of-squares-of-amplitude-errors threshold of the array signal.

[0104] Among them, the second sum of squared amplitude error threshold is a threshold set for the sum of squared amplitude error by analyzing the array signal of the radar in the scenario where the number of signal sources is 2. Similarly, the second sub-mapping relationship corresponding to the number of signal sources being 2 describes the mapping relationship between different signal-to-noise ratios and the second sum of squared amplitude error threshold when the number of signal sources is 2. When it is determined through the first sum of squared amplitude error threshold that the number of signal sources of the array signal is multiple, it is further determined whether the number of signal sources is specifically 2 or greater than 2 through the second sum of squared amplitude error threshold. Specifically, the second sum of squared amplitude error threshold is determined based on the false alarm probability.

[0105] Based on the method provided in this embodiment, it is equivalent to judging the number of signal sources of the array signal with three results through two sums of squared amplitude error thresholds. It can be understood that if a more refined analysis of the number of signal sources is desired, the number of sums of squared amplitude error thresholds can be increased, and each sum of squared amplitude error threshold is associated with the signal-to-noise ratio of the signal. Specifically, the first mapping relationship between the sum of squared amplitude error threshold and the signal-to-noise ratio is determined by obtaining a large number of sample data in each scenario.

[0106] In one embodiment, when it is determined that the signal source of the array signal is not the number of signal sources being 1, in order to estimate the number of signal sources more accurately, other parameters will be set in combination with the second sum of squared amplitude error threshold to analyze the average sum of amplitude error, so as to determine the estimation result of the number of signal sources. Specifically, as Figure 4 shown, estimating the number of signal sources corresponding to the array signal according to the second sum of squared amplitude error threshold of the array signal includes:

[0107] Step 402, based on the second mapping relationship corresponding to the number of signal sources and the second sum of squared amplitude error threshold, determine the target conditional probability corresponding to the number of signal sources; the second mapping relationship includes: the mapping relationship between the second sum of squared amplitude error threshold and the conditional probability;

[0108] Step 404, estimate the number of signal sources corresponding to the array signal according to the target conditional probability corresponding to the number of signal sources.

[0109] Among them, the target conditional probability corresponding to the number of signal sources refers to the probability that the sum of squared amplitude error threshold is greater than the second sum of squared amplitude error threshold under the condition that the number of signal sources of the signal is this number of signal sources. The second mapping relationship corresponding to the number of signal sources is related to the signal-to-noise ratio, and different signal-to-noise ratios correspond to different second sums of squared amplitude error thresholds. Therefore, different conditional probabilities are determined according to different second sums of squared amplitude error thresholds.

[0110] By obtaining the target conditional probability corresponding to the number of signal sources, the posterior probability that the number of signal sources of the array signal is this number of signal sources is determined, thereby determining the number of signal sources of the array signal. The second mapping relationship corresponding to the number of signal sources may include a third sub-mapping relationship corresponding to the number of signal sources being 2, may also include a fourth sub-mapping relationship corresponding to the number of signal sources being greater than or equal to 3, or both. When adopting one of them, the posterior probability when the number of signal sources is this number can be obtained. For example, in one embodiment, through the third sub-mapping relationship corresponding to the number of signal sources being 2, the posterior probability that the number of signal sources of the array signal is 2 is calculated. When this posterior probability meets a preset condition, such as being greater than a preset threshold, it is determined that the number of signal sources of the array signal is 2; otherwise, it is considered that the number of signal sources is greater than or equal to 3. When using both, it is necessary to calculate the posterior probabilities of the two cases where the number of signal sources of the array signal is respectively these two cases, and then take the larger of the two posterior probabilities as the estimation result.

[0111] For example, in one embodiment, the second mapping relationship corresponding to the number of signal sources includes a third sub-mapping relationship corresponding to the number of signal sources being 2; the target conditional probability corresponding to the number of signal sources includes: a first conditional probability that the number of signal sources is 2;

[0112] Estimating the number of signal sources corresponding to the array signal according to the target conditional probability corresponding to the number of signal sources includes:

[0113] According to the first conditional probability corresponding to the array signal, determine the first posterior probability that the number of signal sources of the array signal is 2;

[0114] Based on the first posterior probability that the number of signal sources of the array signal is 2, determine the estimation result of the number of signal sources of the array signal.

[0115] Wherein, the posterior probability of the array signal corresponding to this number of signal sources refers to the probability that the number of signal sources of the array signal is this number of signal sources when it is known that the sum of the squared amplitude errors of the array signal is greater than the second sum-of-squared amplitude-error threshold. When it is known that the sum of the squared amplitude errors of the array signal is greater than the second sum-of-squared amplitude-error threshold, the posterior probability that the number of signal sources of the array signal is this number of signal sources can be determined through the target conditional probability corresponding to the number of signal sources.

[0116] In addition, the target conditional probability corresponding to the number of signal sources can also be determined by the probability distribution information corresponding to the number of signal sources, wherein the probability distribution information corresponding to the number of signal sources is used to describe the value distribution of the sum of the squared amplitude errors corresponding to this number of signal sources.

[0117] Also for example, in one embodiment, as Figure 5 shown, the second mapping relationship corresponding to the number of signal sources includes a fourth sub-mapping relationship corresponding to the number of signal sources being greater than or equal to 3; the target conditional probability corresponding to the number of signal sources includes: a second conditional probability that the number of signal sources is greater than or equal to 3;

[0118] Determine the estimated result of the number of signal sources of the array signal based on the first posterior probability that the number of signal sources of the array signal is 2, including:

[0119] Step 502, determine the second posterior probability that the number of signal sources of the array signal is greater than or equal to 3 according to the second conditional probability corresponding to the array signal;

[0120] Step 504, use the number of signal sources corresponding to the larger value among the first posterior probability and the second posterior probability as the estimated result of the number of signal sources of the array signal.

[0121] It should be noted that the more the second mapping relationships corresponding to the number of signal sources adopted in step 402, the more refined the estimated result of the number of signal sources of the array signal will be. However, when the number of the second mapping relationships corresponding to the number of signal sources adopted exceeds a certain amount, the result will be too refined and the result cannot be accurately obtained through probability. Therefore, it is necessary to select an appropriate number of the second mapping relationships corresponding to the number of signal sources. For example, in the above embodiments, the cases where the number of signal sources is 2 and the number of signal sources is greater than 2 are judged, so as to more accurately determine whether the number of signal sources is 2 or greater than or equal to 3.

[0122] The calculation of the posterior probability can be determined in combination with Bayes' theorem.

[0123] For example, the second mapping relationships corresponding to the number of signal sources include: and .

[0124] According to Bayes' formula, it can be known that:

[0125] ;

[0126] ;

[0127] In the formula, represents the first posterior probability that the number of signal sources is 2 when the sum of the squared amplitude errors is greater than the second sum-of-squared amplitude error threshold; represents the second posterior probability that the number of signal sources is not less than 3 when the sum of the squared amplitude errors is greater than the second sum-of-squared amplitude error threshold; represents the first conditional probability that the sum of the squared amplitude errors is greater than the second sum-of-squared amplitude error threshold when the number of signal sources is 2; represents the first conditional probability that the sum of the squared amplitude errors is greater than the second sum-of-squared amplitude error threshold when the number of signal sources is not less than 3; represents the probability that the signal source is the number of signal sources 2, represents the probability that the number of signal sources is not less than 3, and are both prior probabilities.

[0128] Thus, it can be known that when and In the case where it is possible to determine and , one can obtain and , thereby and . Among them, the number of signal sources corresponding to the larger value in can be determined according to and the signal-to-noise ratio to obtain the third mapping sub-relationship between . During the estimation of the number of signal sources, corresponding to is directly determined. Similarly, can be determined according to and the signal-to-noise ratio to obtain the fourth mapping sub-relationship between . During the estimation of the number of signal sources, corresponding to is directly determined.

[0129] It should be noted that the second mapping relationship corresponding to the number of signal sources is determined according to the simulation experiment data after multiple simulation experiments on radar systems under different signal-to-noise ratios.

[0130] In the method provided in the above embodiment, by combining the Bayesian principle and calculating the posterior probability through conditional probability, the probabilities of the two results can be accurately calculated, so as to more precisely determine the estimated result of the number of signal sources. When greater precision is desired, only multiple second mapping relationships need to be determined in advance, and the probabilities of each result are calculated during the actual estimation process to determine the estimated result.

[0131] In the method for estimating the number of signal sources provided in the above embodiment, if it is necessary to determine the corresponding threshold based on the sum of squared amplitude errors of the array signal and the signal-to-noise ratio to estimate the number of signal sources, the first sub-mapping relationship corresponding to the number of signal sources being 1, the second sub-mapping relationship corresponding to the number of signal sources being 2, the third sub-mapping relationship corresponding to the number of signal sources being 2, and the fourth sub-mapping relationship corresponding to the number of signal sources being greater than or equal to 3 are required. The above mapping relationships are all determined through simulation experiments on the radar system and need to be determined before estimating the number of signal sources in real time.

[0132] In one of the embodiments, the first mapping relationship and the second mapping relationship corresponding to the number of signal sources are constructed based on at least part of the simulation data in the simulation data set obtained by simulation under the number of signal sources; the simulation data set includes: the sum of squared amplitude error simulation data obtained by simulating the sample radar under different signal-to-noise ratios under the number of signal sources, and the corresponding signal-to-noise ratio.

[0133] Under the condition of setting the number of signal sources, a simulation experiment is carried out on the sample radar to obtain a simulation data set, so as to determine various mapping relationships corresponding to the number of signal sources. Among them, the parameters of the sample radar are the same as those of the radar for obtaining the array signal in the above embodiment, such as the structure of the array antenna. The simulation methods include but are not limited to mathematical simulation, semi-physical simulation, physical simulation, software simulation and other methods. When carrying out the simulation experiment, since the first mapping relationship includes the relationship between the signal-to-noise ratio and the threshold of the sum of squared amplitude errors, and the second mapping relationship also involves the signal-to-noise ratio. Therefore, in the experiment, the signal-to-noise ratio of the array signal is adjusted, and multiple data acquisitions are carried out at different signal-to-noise ratios to construct a simulation data set, and then various mapping relationships corresponding to the number of signal sources are determined based on the simulation data set.

[0134] Among them, different signal-to-noise ratios may be randomly generated signal-to-noise ratios with different magnitudes; the relationship between different signal-to-noise ratios in this way is random, and multiple simulation data are obtained under each random signal-to-noise ratio to characterize the overall characteristics of the array signal under that signal-to-noise ratio. Different signal-to-noise ratios can also be changed according to a setting. For example, in one embodiment, different signal-to-noise ratios form an arithmetic sequence of data, such as randomly generating SNR=(0:5:40)dB, and similarly, multiple simulation data are obtained under each signal-to-noise ratio.

[0135] In the simulation data set, it includes multiple sum-of-squared amplitude error simulation values obtained under each signal-to-noise ratio, and the mapping relationship refers to the relationship between the signal-to-noise ratio and the threshold of the sum of squared amplitude errors. Therefore, it is necessary to determine the corresponding sum-of-squared amplitude error threshold simulation value according to the multiple sum-of-squared amplitude error simulation values corresponding to the signal-to-noise ratio, so as to perform relationship mapping.

[0136] Among them, the sum-of-squared amplitude error threshold simulation value corresponding to the signal-to-noise ratio can be a new value obtained after a certain process on the multiple sum-of-squared amplitude error simulation values corresponding to the signal-to-noise ratio, as the sum-of-squared amplitude error threshold simulation value; at this time, all the simulation data in the simulation data set are used to determine the mapping relationship. Or select a part of the multiple sum-of-squared amplitude error simulation values for processing to obtain the sum-of-squared amplitude error threshold simulation value. At this time, using part of the simulation data in the simulation data set, the mapping relationship can be determined.

[0137] When determining the mapping relationship according to part of the simulation data, part of the simulation data includes at least one sum-of-squared amplitude error simulation value corresponding to each signal-to-noise ratio among different signal-to-noise ratios. For example, select a specific sum-of-squared amplitude error simulation value from the multiple sum-of-squared amplitude error simulation values corresponding to the signal-to-noise ratio as the sum-of-squared amplitude error threshold simulation value corresponding to the signal-to-noise ratio. The specific sum-of-squared amplitude error simulation value includes: the sum-of-squared amplitude error simulation value at the first preset position after sorting the multiple sum-of-squared amplitude error simulation values corresponding to the signal-to-noise ratio according to the first preset rule.

[0138] Among them, the first preset rule refers to the variation rule of the sum of squared amplitude errors in simulation, including the variation from large to small or from small to large.

[0139] To facilitate the understanding of the determination process of the multiple mapping relationships described above, it will be described in combination with the following specific embodiments.

[0140] Suppose is the number of signal sources, and the following mixed binary estimation problem is established:

[0141] ;

[0142] ;

[0143] Among them, represents the hypothesis that the number of signal sources is 1, represents the hypothesis that the number of signal sources is greater than or equal to 2, and assume that contains two sub-hypotheses, represents the hypothesis that the number of signal sources is 2, represents the hypothesis that the number of signal sources is greater than or equal to 3.

[0144] According to , set the first false alarm probability , conduct Monte Carlo experiments, randomly generate simulation parameters with the number of signal sources being 1 at different typical signal-to-noise ratios, and conduct simulation experiments on the radar system with the number of signal sources being 1. Sort the sum of squared amplitude error simulation data at each signal-to-noise ratio obtained from large to small to form a vector , and the first sum of squared amplitude error threshold can be set as:

[0145] ;

[0146] Among them, is the th element in the vector The size of is determined based on the number of experiments and the first false alarm probability Take 101 in one embodiment, then set the 101st element in the vector as the first sum of squared amplitude error threshold simulation value.

[0147] After determining the simulation values of the first sum of squared amplitude error thresholds corresponding to all signal-to-noise ratios, the mapping relationship between the first sum of squared amplitude error threshold and the signal-to-noise ratio can be determined, that is, the first sub-mapping relationship corresponding to a source number of 1. For example, in one embodiment, the form of the first sub-mapping relationship corresponding to a source number of 1 is a function expression. Determining the first sub-mapping relationship corresponding to a source number of 1 based on the simulation values of the first sum of squared amplitude error thresholds corresponding to all signal-to-noise ratios includes:

[0148] Based on a preset function expression, fitting according to the simulation values of the first sum of squared amplitude error thresholds corresponding to all signal-to-noise ratios to obtain the function expression between the first sum of squared amplitude error threshold and the signal-to-noise ratio.

[0149] For example, the preset function expression is a power exponent. Fitting through the simulation values of the first sum of squared amplitude error threshold and the corresponding signal-to-noise ratio to obtain fitting parameters a, b, c:

[0150] ;

[0151] After the above fitting parameters a, b, c are determined, the function expression between the first sum of squared amplitude error threshold and the signal-to-noise ratio can be determined and stored in the radar memory, and can be directly called during actual application; the fitting parameters and the power exponent function can also be stored in the radar memory at the same time, and the fitting parameters and the corresponding function type can be called at the same time during actual application.

[0152] Similarly, according to , setting the second false alarm probability , doing Monte Carlo experiments, randomly generating simulation parameters with a source number of 2 under different typical signal-to-noise ratios, and conducting a simulation experiment with a source number of 2 on the radar system. Sort the simulation data of the sum of squared amplitude errors obtained at each signal-to-noise ratio from large to small to form a vector , and the second sum of squared amplitude error threshold can be set as:

[0153] ;

[0154] Among them, is the number of cases where the sum of squared amplitude errors at this signal-to-noise ratio is greater than the first sum of squared amplitude error threshold .

[0155] Similarly, the function expression between the second sum of squared amplitude error threshold and the signal-to-noise ratio can be fitted based on the power exponent function to obtain fitting parameters and stored in the radar memory.

[0156] The determination process of the third sub-mapping relationship corresponding to a source number of 2 includes: obtaining, according to the simulation data with a source number of 2, at each signal-to-noise ratio When determining the number of signal sources as 2, for each signal-to-noise ratio, the corresponding first conditional probability The relationship fitted with the signal-to-noise ratio is stored in the radar memory.

[0157] The fourth sub-mapping relationship corresponding to the number of signal sources greater than or equal to 3 includes:

[0158] According to set the second false alarm probability , conduct Monte Carlo experiments. Randomly generate simulation parameters under different typical signal-to-noise ratios, and conduct simulation experiments on the radar system with the number of signal sources greater than or equal to 3. Sort the sum of squared amplitude errors and simulation data at each signal-to-noise ratio obtained from largest to smallest to form a vector When determining the number of signal sources greater than or equal to 3, for each signal-to-noise ratio, the corresponding second conditional probability The relationship fitted with the signal-to-noise ratio is stored in the radar memory.

[0159] The method for estimating the number of signal sources provided in the embodiments of the present application pre-trains the first sub-mapping relationship corresponding to the number of signal sources being 1 between the signal-to-noise ratio and the first sum-of-squared amplitude error threshold, the second sub-mapping relationship corresponding to the number of signal sources being 2 between the signal-to-noise ratio and the second sum-of-squared amplitude error threshold, the third mapping sub-relationship corresponding to the number of signal sources being 2 between the second sum-of-squared amplitude error and the conditional probability, and the fourth mapping sub-relationship corresponding to the number of signal sources greater than or equal to 3 between the second sum-of-squared amplitude error and the conditional probability. When estimating the number of signal sources of the array signal, based on the signal-to-noise ratio of the array signal, determine the corresponding first sum-of-squared amplitude error threshold and second sum-of-squared amplitude error threshold, and combine the sum of squared amplitude errors of the array signal to estimate the number of signal sources. It can adaptively determine the corresponding threshold according to the signal-to-noise ratio, reducing the influence of the signal-to-noise ratio on the result of estimating the number of signal sources. Moreover, the method of this embodiment does not require calculating the covariance matrix to estimate the number of signal sources, greatly reducing the amount of computation. In addition, the method provided in the embodiments of the present application is applicable to sparse arrays and single snapshot array signals, and can estimate the number of signal sources being 1, the number of signal sources being 2, and the number of signal sources greater than or equal to 3 simultaneously in the case of sparse arrays.

[0160] The following provides several specific embodiments to further illustrate the method provided in the present application.

[0161] Assume that the configuration of the array antenna is the minimum redundancy array with 8 array elements, and the corresponding array aperture is [0, 1, 2, 11, 15, 18, 21, 23] * 0.5λ. Assume that the virtual receiving steering vector of the signal is , and the received signal is:

[0162] ,

[0163] Among them, is the number of signal sources, is the th signal source. The expression for calculating the sum of squared amplitude errors of the array signal is:

[0164] ;

[0165] Among them, is the number of array elements in the radar's array antenna, represents the amplitude of the received signal of the th array element, represents the mean value of the amplitudes of the received signals of all array elements.

[0166] Set the first false alarm probability , conduct Monte Carlo experiments, randomly generate simulation parameters with the number of signal sources SNR = (0:5:40) dB being 1, and conduct a simulation experiment on the radar system with the number of signal sources being 1. Sort the simulation data of the sum of squared amplitude errors at each signal-to-noise ratio obtained from largest to smallest to form a vector , and the first sum-of-squared amplitude error threshold can be set as:

[0167] ;

[0168] Obtain the simulation values of the first sum-of-squared amplitude error threshold corresponding to different signal-to-noise ratios, perform power-law exponential fitting, and obtain fitting parameters a1 = -0.7522, b1 = -0.7123, c = 2.5236. Figures 6(a)-(b) are the simulation results with the number of signal sources being 1. Among them, Figure 6(a) is the fitting curve of SNR and the first sum-of-squared amplitude error threshold, where a1 = -0.7522, b1 = -0.7123, c = 2.5236. Figure 6(b) is the success rate curve of estimating the number of signal sources being 1. Within the typical SNR setting range, the success rate has been above 90%, and the success rate is relatively high. It can be seen that the process of the present invention can accurately determine that the number of signal sources is 1. It can be seen that the process of the present invention can accurately determine that the number of signal sources is 1.

[0169] For the above array antenna, according to , set the second false alarm probability , conduct Monte Carlo experiments, randomly generate simulation parameters with the number of signal sources SNR = (0:5:40) dB being 2, and conduct a simulation experiment on the radar system with the number of signal sources being 2. Sort the simulation data of the sum of squared amplitude errors at each signal-to-noise ratio obtained from largest to smallest to form a vector , and the second sum-of-squared amplitude error threshold can be set as:

[0170] ;

[0171] The fitting parameters between the second sum of squared amplitude errors threshold and the signal-to-noise ratio are obtained by fitting as a2 = 1.0652 and b2 = 4.2713.

[0172] And according to , the third sub-mapping relationship between the second sum of squared amplitude errors threshold at SNR=(0:5:40) dB and the first conditional probability with the number of signal sources being 2 is determined; and according to , the second false alarm probability is set , and Monte Carlo experiments are performed to determine the fourth sub-mapping relationship between the second sum of squared amplitude errors threshold at SNR=(0:5:40) dB and the second conditional probability with the number of signal sources greater than or equal to

[0173] Fig. 7(a) shows the probability of passing the first sum of squared amplitude errors threshold when the number of signal sources is 2. From this figure, it can be obtained that when the number of signal sources is 2 and SNR≥10, the probability of passing the first sum of squared amplitude errors threshold is greater than 90%, and when SNR≥20, the probability of passing the first sum of squared amplitude errors threshold is stable at about 100%. Thus, the probability of passing the first sum of squared amplitude errors threshold is relatively high when the number of signal sources is 2. Fig. 7(b) is the fitting curve of SNR and the second sum of squared amplitude errors threshold, and the fitting results are a = 1.0652 and b = 4.2713. Fig. 7(c) is the estimated success rate curve when the number of signal sources is 2. From this simulation, it can be seen that when SNR is greater than or equal to 10 dB, the success rate is greater than 80%, and when SNR is greater than 15 dB, the success rate is stable above 90%, and the success rate is relatively high. It can be seen that the process of the present invention can accurately determine that the number of signal sources is 2.

[0174] Fig. 8(a) shows the probability of passing the first sum of squared amplitude errors threshold when the number of signal sources is greater than or equal to 3. From this figure, it can be obtained that the probability of passing the first sum of squared amplitude errors threshold is 100% (SNR≥10) when the number of signal sources is greater than or equal to 3. Fig. 8(b) is the probability curve of correct detection when the number of signal sources is greater than or equal to 3. From this simulation, it can be seen that the success rate of detection when the number of signal sources is greater than or equal to 3 is always above 80% at typical SNR=(0:5:40) dB, and the success rate is relatively high. It can be seen that the process of the present invention can accurately determine that the number of signal sources is greater than or equal to 3.

[0175] Combining the above inventive concepts, in one embodiment, the embodiment of the present application provides a method for estimating the direction of arrival, as Figure 9 shown, the method includes:

[0176] Step 902, obtaining the array signal of the radar;

[0177] Step 904: Determine the target mean squared amplitude error threshold corresponding to the number of signal sources based on the mapping relationship corresponding to the number of signal sources and the target signal-to-noise ratio of the array signal; the mapping relationship includes: the mapping relationship between the signal-to-noise ratio of the signal source and the mean squared amplitude error threshold.

[0178] Step 906: Estimate the number of signal sources corresponding to the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the number of signal sources.

[0179] Step 908: Estimate the direction of arrival of the signal of the array signal according to the estimation result of the number of signal sources of the array signal.

[0180] The direction-of-arrival estimation method provided in the above embodiments obtains the array signal of the radar, calculates the mean squared amplitude error and the signal-to-noise ratio of the array signal; based on the first sub-mapping relationship corresponding to 1 signal source for the number of signal sources, determine the first mean squared amplitude error threshold corresponding to the signal-to-noise ratio, and the first mean squared amplitude error threshold is used to indicate the magnitude of the mean squared amplitude error. The first sub-mapping relationship corresponding to 1 signal source for the number of signal sources is determined based on the simulation data with 1 signal source for the radar; estimate the number of signal sources of the array signal according to the mean squared amplitude error and the first mean squared amplitude error threshold; according to the estimation result of the number of signal sources of the array signal, select an appropriate algorithm to estimate the direction of arrival of the signal. By determining the adaptive first mean squared amplitude error threshold through the signal-to-noise ratio of the array signal and judging the mean squared amplitude error of the array signal, the estimation of the number of signal sources of the array signal is realized, which can effectively reduce the influence of the signal-to-noise ratio on the accuracy of the estimation result of the number of signal sources, thereby improving the accuracy of the direction-of-arrival estimation result.

[0181] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0182] Based on the same inventive concept, an embodiment of the present application further provides a source number estimation device. The implementation solution provided by this device for solving problems is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the source number estimation device provided below can refer to the limitations on the source number estimation method in the foregoing, and will not be elaborated herein.

[0183] In one embodiment, as Figure 10 shown, the source number estimation device includes an acquisition module 1001, a determination module 1002, and an estimation module 1003, where:

[0184] The acquisition module 1001 is configured to acquire the array signal of the radar;

[0185] The determination module 1002 is configured to determine the target mean squared amplitude error threshold corresponding to the source number based on the first mapping relationship corresponding to the source number and the target signal-to-noise ratio of the array signal; the first mapping relationship includes: the mapping relationship between the source signal-to-noise ratio and the mean squared amplitude error threshold;

[0186] The estimation module 1003 is configured to estimate the source number of the array signal according to the mean squared amplitude error of the array signal and the target mean squared amplitude error threshold corresponding to the source number.

[0187] In a possible implementation manner, the mapping relationship corresponding to the source number includes a first sub-mapping relationship corresponding to a source number of 1; the target mean squared amplitude error threshold corresponding to the source number includes: a first mean squared amplitude error threshold corresponding to a source number of 1; the estimation module 1003 is further configured to:

[0188] When the mean squared amplitude error of the array signal is less than or equal to the first mean squared amplitude error threshold, determine that the source number of the array signal is 1;

[0189] When the mean squared amplitude error of the array signal is greater than the first mean squared amplitude error threshold, determine that the source number of the array signal is greater than 1.

[0190] In a possible implementation manner, the first mapping relationship corresponding to the source number includes a second sub-mapping relationship corresponding to a source number of 2; the target mean squared amplitude error threshold corresponding to the source number includes: a second mean squared amplitude error threshold corresponding to a source number of 2; the estimation module 1003 is further configured to:

[0191] When the mean squared amplitude error of the array signal is greater than the first mean squared amplitude error threshold, estimate the source number corresponding to the array signal according to the second mean squared amplitude error threshold of the array signal.

[0192] In a possible implementation manner, the estimation module 1003 is further configured to:

[0193] Based on the second mapping relationship corresponding to the number of signal sources and the second sum of squared amplitude error threshold, determine the target conditional probability corresponding to the number of signal sources; the second mapping relationship includes: the mapping relationship between the second sum of squared amplitude error threshold and the conditional probability.

[0194] Estimate the number of signal sources corresponding to the array signal according to the target conditional probability corresponding to the number of signal sources.

[0195] In a possible implementation manner, the second mapping relationship corresponding to the number of signal sources includes a third sub-mapping relationship corresponding to the number of signal sources being 2; the target conditional probability corresponding to the number of signal sources includes: the first conditional probability when the number of signal sources is 2; the estimation module 1003 is further configured to:

[0196] Determine the first posterior probability that the number of signal sources of the array signal is 2 according to the first conditional probability corresponding to the array signal.

[0197] Based on the first posterior probability that the number of signal sources of the array signal is 2, determine the estimation result of the number of signal sources of the array signal.

[0198] In a possible implementation manner, the second mapping relationship corresponding to the number of signal sources includes a fourth sub-mapping relationship corresponding to the number of signal sources being greater than or equal to 3; the target conditional probability corresponding to the number of signal sources includes: the second conditional probability when the number of signal sources is greater than or equal to 3; the estimation module 1003 is further configured to:

[0199] Based on the first posterior probability that the number of signal sources of the array signal is 2, determining the estimation result of the number of signal sources of the array signal includes:

[0200] Determine the second posterior probability that the number of signal sources of the array signal is greater than or equal to 3 according to the second conditional probability corresponding to the array signal.

[0201] Use the number of signal sources corresponding to the larger value between the first posterior probability and the second posterior probability as the estimation result of the number of signal sources of the array signal.

[0202] In a possible implementation manner, the determination module 1002 is further configured to determine that: the first mapping relationship and the second mapping relationship corresponding to the number of signal sources are constructed based on at least part of the simulation data in the simulation data set obtained by simulation under the number of signal sources; the simulation data set includes: the sum of squared amplitude error simulation data obtained by simulating the sample radar under the number of signal sources using different signal-to-noise ratios, and the corresponding signal-to-noise ratios.

[0203] In a possible implementation manner, the determination module 1002 is further configured to determine that: the simulation data set includes multiple sum of squared amplitude error simulation values corresponding to different signal-to-noise ratios, and at least part of the simulation data includes at least one sum of squared amplitude error simulation value corresponding to each signal-to-noise ratio among different signal-to-noise ratios.

[0204] The at least one sum of squared amplitude error simulation value corresponding to the signal-to-noise ratio includes: the sum of squared amplitude error simulation value at the first preset position after sorting the multiple sum of squared amplitude error simulation values corresponding to the signal-to-noise ratio according to the first preset rule.

[0205] In a possible implementation manner, the determining module 1002 is further configured to determine that: the first preset position is determined based on the number of experiments of the simulation experiment and the false alarm probability.

[0206] In a possible implementation manner, the determining module 1002 is further configured to determine that: the first mapping relationship and the second mapping relationship corresponding to the number of signal sources are function expressions obtained by fitting based on at least part of the simulation data in the simulation data set obtained by simulation under the number of signal sources.

[0207] In a possible implementation manner, the determining module 1002 is further configured to determine that: the different signal-to-noise ratios included in the simulation data set form an arithmetic sequence.

[0208] In a possible implementation manner, the obtaining module 1001 is further configured to determine that: the radar is a sparse array.

[0209] In a possible implementation manner, the obtaining module 1001 is further configured to determine that: the array signal of the radar is a single snapshot signal.

[0210] Each module in the above-mentioned number-of-signal-sources estimation device can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor in the computer device in hardware form or be independent of it, or can be stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0211] In an embodiment, there is also provided a radar system, which includes a signal transmitter, an array antenna, and a signal processor; the signal transmitter is used to transmit signals, and the array antenna is used to receive signals;

[0212] The signal processor is used to construct an array signal according to the received signal and estimate the number of signal sources of the array signal, and is specifically used for the method steps in the above-mentioned number-of-signal-sources estimation method and / or direction-of-arrival estimation method.

[0213] In an embodiment, there is also provided a vehicle, which includes the above-mentioned radar system.

[0214] Figure 11 It is a schematic structural diagram of the electronic device provided by this application. As Figure 11As shown in the figure, the electronic device 110 provided in this embodiment includes: at least one processor 1101 and a memory 1102. Optionally, the device 110 further includes a communication component 1103. Among them, the processor 1101, the memory 1102, and the communication component 1103 are connected through a bus 1104.

[0215] In a specific implementation process, at least one processor 1101 executes the computer-executable instructions stored in the memory 1102, so that at least one processor 1101 executes the above-mentioned method.

[0216] For the specific implementation process of the processor 1101, reference can be made to the above method embodiment. The implementation principle and technical effects are similar, and will not be elaborated here in this embodiment.

[0217] In the above embodiment, it should be understood that the processor may be a central processing unit (Central Processing Unit, CPU for short), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP for short), application-specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0218] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0219] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, the buses in the drawings of this application are not limited to only one bus or one type of bus.

[0220] This application also provides a computer program product, including a computer program, which implements the above-mentioned method when executed by a processor.

[0221] The present application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0222] The above-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disk. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0223] An exemplary readable storage medium is coupled to the processor so that the processor can read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in a device.

[0224] The division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0225] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0226] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0227] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, and other various media that can store program codes.

[0228] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When this program is executed, it executes the steps including the above method embodiments; and the aforementioned storage medium includes: ROMs, RAMs, magnetic disks, or optical discs, and other various media that can store program codes.

[0229] Finally, it should be noted that: After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily think of other implementation manners of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, and these variations, uses, or adaptations follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field of the present invention that are not disclosed in the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A method for estimating the number of information sources, characterized in that: The method comprises: Acquire radar array signals; Based on a first mapping relationship corresponding to the number of information sources and a target signal-to-noise ratio of the array signal, a target amplitude error square sum threshold corresponding to the number of information sources is determined; the first mapping relationship includes: a mapping relationship between the signal-to-noise ratio of the information source and the amplitude error square sum threshold; The number of information sources corresponding to the array signal is estimated according to the sum of square amplitude errors of the array signal and a target sum of square amplitude errors threshold corresponding to the number of information sources.

2. The method according to claim 1, characterized in that The first mapping relationship corresponding to the number of information sources includes a first sub-mapping relationship corresponding to the number of information sources being 1; the target amplitude error square sum threshold corresponding to the number of information sources includes: the first amplitude error square sum threshold corresponding to the number of information sources being 1; The estimating the number of information sources corresponding to the array signal according to the sum of squares of amplitude errors of the array signal and a target sum of squares of amplitude errors corresponding to the number of information sources comprises: When the sum of squares of amplitude errors of the array signal is less than or equal to the first sum of squares of amplitude errors threshold, determining the number of information sources of the array signal to be 1; When the sum of square amplitude errors of the array signal is greater than the first sum of square amplitude errors threshold, it is determined that the number of information sources of the array signal is greater than 1.

3. The method according to claim 2, characterized in that The first mapping relationship corresponding to the number of information sources includes a second sub-mapping relationship corresponding to the number of information sources being 2; the target amplitude error square sum threshold corresponding to the number of information sources includes: the second amplitude error square sum threshold corresponding to the number of information sources being 2; The estimating the number of information sources corresponding to the array signal according to the sum of squares of amplitude errors of the array signal and a target sum of squares of amplitude errors corresponding to the number of information sources comprises: When the sum of square amplitude errors of the array signal is greater than the first sum of square amplitude errors threshold, the number of information sources corresponding to the array signal is estimated according to the second sum of square amplitude errors threshold.

4. The method according to claim 3, characterized in that The estimating the number of information sources corresponding to the array signal according to the second amplitude error square sum threshold comprises: Determine the target conditional probability corresponding to the number of information sources based on the second mapping relationship corresponding to the number of information sources and the second amplitude error square sum threshold; the second mapping relationship includes: a mapping relationship between the second amplitude error square sum threshold and the conditional probability; The number of information sources corresponding to the array signal is estimated according to the target conditional probability corresponding to the number of information sources.

5. The method according to claim 4, characterized in that The second mapping relationship corresponding to the number of information sources includes a third sub-mapping relationship corresponding to the number of information sources being 2; the target conditional probability corresponding to the number of information sources includes: a first conditional probability that the number of information sources is 2; The estimating the number of information sources corresponding to the array signal according to the target conditional probability corresponding to the number of information sources includes: Determine a first posterior probability that the number of information sources of the array signal is 2 according to a first conditional probability corresponding to the array signal; Based on the first a posteriori probability that the number of information sources of the array signal is 2, an estimation result of the number of information sources of the array signal is determined.

6. The method according to claim 5, characterized in that The second mapping relationship corresponding to the number of information sources includes a fourth sub-mapping relationship corresponding to the number of information sources being greater than or equal to 3; the target conditional probability corresponding to the number of information sources includes: a second conditional probability that the number of information sources is greater than or equal to 3; The determining, based on the first a posteriori probability that the number of information sources of the array signal is 2, an estimation result of the number of information sources of the array signal comprises: Determining a second posterior probability that the number of information sources of the array signal is greater than or equal to 3 according to a second conditional probability corresponding to the array signal; The number of information sources corresponding to the larger value of the first a posteriori probability and the second a posteriori probability is used as the estimation result of the number of information sources of the array signal.

7. The method according to any one of claims 1 to 6, characterized in that: The first mapping relationship and the second mapping relationship corresponding to the number of information sources are constructed based on at least part of the simulation data in the simulation data set obtained by simulation under the number of information sources; the simulation data set includes: amplitude error square sum simulation data obtained by simulating the sample radar using different signal-to-noise ratios under the number of information sources, and the corresponding signal-to-noise ratio.

8. The method according to claim 7, characterized in that The simulation data set includes a plurality of amplitude error squared simulation values ​​corresponding to different signal-to-noise ratios, and the at least part of the simulation data includes at least one amplitude error squared simulation value corresponding to each of the different signal-to-noise ratios; The at least one amplitude error square sum simulation value corresponding to the signal-to-noise ratio comprises: an amplitude error square sum simulation value at a first preset position after sorting multiple amplitude error square sum simulation values ​​corresponding to the signal-to-noise ratio according to a first preset rule.

9. The method according to claim 8, characterized in that The first preset position is determined based on the number of experiments and the false alarm probability of the simulation experiment.

10. The method according to claim 7, characterized in that The first mapping relationship and the second mapping relationship corresponding to the number of information sources are function expressions obtained by fitting at least part of the simulation data in the simulation data set obtained by simulation under the number of information sources.

11. The method according to claim 7, characterized in that The different signal-to-noise ratios included in the simulation data set are an arithmetic progression.

12. The method according to any one of claims 1 to 6, characterized in that: The radar is a sparse array.

13. The method according to claim 12, characterized in that The array signal of the radar is a single snapshot signal.

14. A method for estimating a direction of arrival, characterized in that: The method comprises: Obtaining a signal source number estimation result of the array signal obtained by the method according to any one of claims 1 to 13; According to the information source number estimation result of the array signal, the signal arrival direction of the array signal is estimated.

15. A signal source number estimation device, characterized in that: The device comprises: An acquisition module, used to acquire the array signal of the radar; A determination module, configured to determine a target amplitude error square sum threshold corresponding to the number of information sources based on a first mapping relationship corresponding to the number of information sources and a target signal-to-noise ratio of the array signal; the first mapping relationship includes: a mapping relationship between the signal-to-noise ratio of the information source and the amplitude error square sum threshold; The estimation module is used to estimate the number of information sources of the array signal according to the sum of squares of amplitude errors of the array signal and a target sum of squares of amplitude errors corresponding to the number of information sources.

16. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 14 when executed by a processor.

18. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 14.

19. A radar system, characterized in that: The radar system includes a signal transmitter, an array antenna and a signal processor; the signal transmitter is used to transmit signals, and the array antenna is used to receive signals; The signal processor is used to construct an array signal according to the received signal, and estimate the number of signal sources of the array signal by using the method according to any one of claims 1 to 14.

20. A vehicle, characterized in that: The vehicle comprises the radar system of claim 19.

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