CN113030941B

CN113030941B - Method, device, equipment and storage medium for determining azimuth angle of target object

Info

Publication number: CN113030941B
Application number: CN202110171713.4A
Authority: CN
Inventors: 张小龙; 陈熠
Original assignee: Calterah Semiconductor Technology Shanghai Co Ltd
Current assignee: Calterah Semiconductor Technology Shanghai Co Ltd
Priority date: 2020-02-28
Filing date: 2021-02-08
Publication date: 2024-03-22
Anticipated expiration: 2041-02-08
Also published as: CN113030941A

Abstract

The application relates to a method, a device, computer equipment, a storage medium, an integrated circuit, a radio device, a sensor and equipment for determining an azimuth angle of a target object, and relates to the technical field of target detection. The azimuth determining method of the target comprises the steps of obtaining a preset angle set to be searched; obtaining the number N of target objects; sequentially performing at least two-stage N-dimensional search on the angle set to be searched based on maximum likelihood estimation; based on the result of the last-stage N-dimensional search, acquiring azimuth angles of all targets; wherein, there is at least one level N dimension search in at least two levels of N dimension searches, when searching for the same level N dimension search in the at least one level N dimension search many times, the initial values of at least two times of searches are different. By enabling the initial values of the searches to be different, the search of the level can be effectively prevented from being trapped into the local extreme point search, so that the probability that the global maximum value can be obtained by searching the angle set to be searched by maximum likelihood estimation is improved.

Description

Method, device, equipment and storage medium for determining azimuth angle of target object

The present application claims priority from the chinese patent office, application number 202010131565.9, title of the invention "method, apparatus, device and storage medium for determining azimuth of target object" at 28, month 02, 2020, and the chinese patent office, application number 202010131569.7, title of the invention "method, apparatus, device and storage medium for determining azimuth of target object" at 28, month 02, 2020, the entire contents of which are incorporated herein by reference.

Technical Field

The present disclosure relates to the field of target detection technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, an integrated circuit, a radio device, a sensor, and a device for determining an azimuth angle of a target object.

Background

In target detection using a sensor (e.g., FMCW radar, etc.), maximum likelihood estimation (Maximum likelihood estimation, MLE) is typically used to determine the azimuth of the target. When determining the azimuth angle of the target object by using the MLE, generally, different angular vectors to be searched are input into a preset search model to obtain model output results corresponding to the angular vectors to be searched, the target model output results are selected from the model output results, and the azimuth angle is obtained according to the angular vectors to be searched corresponding to the target model output results.

However, since the set of angles to be searched is searched by adopting the fixed initial position, the search is easy to sink into the search of local extremum points, and the global maximum value cannot be obtained.

Disclosure of Invention

Based on this, there is a need to provide a method, apparatus, device and storage medium for determining azimuth angle of object, integrated circuit radio device, sensor and device for solving the problem that the searching in the above prior art is easy to fall into local extremum point searching and cannot obtain global maximum.

In a first aspect, a method for determining azimuth of a target, the method comprising:

acquiring a preset angle set to be searched;

obtaining the number N of target objects;

sequentially performing at least two-stage N-dimensional search on the angle set to be searched based on maximum likelihood estimation; and

acquiring azimuth angles of all targets based on the result of the last-stage N-dimensional search;

wherein, there is at least one level N dimension searching in at least two levels of N dimension searching, when searching for the same level N dimension searching in the at least one level N dimension searching many times, the initial values of at least two times of searching are different; n is an integer greater than or equal to 2.

In this embodiment, when N-dimensional searches of each level are sequentially performed on the angle set to be searched based on the maximum likelihood estimation, the search of the level can be effectively prevented from being trapped into the local extremum point search by making the initial values of searches with different times different for the N-dimensional searches of the same level, compared with the conventional search using a fixed initial position, so as to improve the probability that the global maximum value can be obtained by searching the angle set to be searched using the maximum likelihood estimation.

In one embodiment, in at least two levels of N-dimensional searches, when a plurality of searches are performed for any one level of N-dimensional search, the start values of at least two searches are different.

In this embodiment, in performing N-dimensional searches at each level, there are different initial values of at least two searches in multiple searches for N-dimensional searches at the same level, so as to further improve the probability that the global maximum value can be obtained by searching the angle set to be searched by using maximum likelihood estimation.

In one embodiment, at least one level of N-dimensional search exists in at least two levels of N-dimensional searches, and when multiple searches are performed for the same level of N-dimensional search in the at least one level of N-dimensional search, the initial values of the multiple searches are different.

In this embodiment, the probability that the global maximum value can be obtained by searching the angle set to be searched by using the maximum likelihood estimation can be further improved.

In one embodiment, in at least two levels of N-dimensional searches, the start values of the searches are different from one search to another.

In this embodiment, it may be ensured that searching the set of angles to be searched using maximum likelihood estimation may result in a global maximum.

In one embodiment, the method may further include:

and aiming at the N-dimensional search of the same level, carrying out multiple searches by adopting the same interval value.

In this embodiment, in multiple searches for the same level N-dimensional search, multiple searches are performed using the same interval value, so that it is ensured that searching for the angle set to be searched using maximum likelihood estimation can obtain a global maximum value.

In one embodiment, the set of angles to be searched includes a plurality of preset angles to be searched distributed according to the equal function difference, and the number of the plurality of preset angles to be searched is greater than N.

In this embodiment, the set of angles to be searched includes a plurality of preset angles to be searched distributed according to the equal function difference, that is, the interval value of N-dimensional searches at each level is also adaptively set according to the equal function difference, and the number of the plurality of preset angles to be searched is greater than N, so as to reduce the iterative operand of the maximum likelihood estimation process.

In one embodiment, sequentially performing at least two levels of N-dimensional search on the angle set to be searched based on maximum likelihood estimation includes:

for an mth level N-dimensional search in at least two levels of N-dimensional searches, determining a search angle vector set of the mth level N-dimensional search according to target search angle vectors of the mth-1 level N-dimensional search, wherein the search angle vector set of the mth level N-dimensional search comprises a plurality of search angle vectors, and each search angle vector comprises N angles; m is an integer greater than or equal to 1;

inputting the search angle vector set of the m-th level N-dimensional search into a preset search model to obtain an output result of the m-th level N-dimensional search;

determining a target search angle vector of the m-th level N-dimensional search according to the output result of the m-th level N-dimensional search;

If the m-th level N-dimensional search is the last level N-dimensional search of at least two levels of N-dimensional searches, taking the output result of the m-th level N-dimensional search as the result of the last level N-dimensional search; if the m-th level N-dimensional search is the first level N-dimensional search of at least two levels of N-dimensional searches, determining a search angle vector set of the m-th level N-dimensional search according to a preset angle set to be searched.

In one embodiment, determining a set of search angle vectors for an m-th level N-dimensional search from target search angle vectors for the m-1-th level N-dimensional search includes:

determining a candidate angle range according to a target search angle vector of the m-1 level N-dimensional search;

determining a plurality of angles to be searched distributed according to the equal function difference value from the candidate angle range;

and determining a search angle vector set of the m-th level N-dimensional search according to the plurality of angles to be searched.

In a second aspect, an azimuth determining device for a target, the device comprising:

the first acquisition module is used for acquiring a preset angle set to be searched;

the second acquisition module is used for acquiring the number N of the target objects;

the searching module is used for sequentially carrying out at least two-stage N-dimensional searching on the angle set to be searched based on the maximum likelihood estimation; and

the azimuth determining module is used for acquiring azimuth angles of all targets based on the result of the last-stage N-dimensional search;

In a third aspect, a computer device comprises a memory storing a computer program and a processor implementing the method steps of the first aspect described above when the processor executes the computer program.

In a fourth aspect, a computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the method steps of the first aspect described above.

In a fifth aspect, an integrated circuit, comprising:

a signal receiving and transmitting channel for transmitting radio signals and receiving echo signals;

the analog-to-digital circuit module is used for carrying out analog-to-digital conversion on the echo information to generate a digital signal; and

the digital signal processing module is used for acquiring a preset angle set to be searched based on the digital signal; obtaining the number N of target objects; performing N-dimensional search on the angle set to be searched based on maximum likelihood estimation; based on the N-dimensional search result, acquiring azimuth angles of all targets;

Performing N-dimensional search on the angle set to be searched based on maximum likelihood estimation, wherein the N-dimensional search comprises first-stage search and second-stage search; in the first level search, the initial values of the searches are different; the result of the second level N-dimensional search is used to obtain the azimuth of each target.

In one embodiment, the radio signal is a millimeter wave signal; and/or

The to-be-searched angle set comprises a plurality of preset to-be-searched angles distributed according to the equal function difference value, N is an integer greater than or equal to 2, and the number of the plurality of preset to-be-searched angles is greater than N.

In a sixth aspect, a radio device includes:

a carrier;

an integrated circuit as in the fifth aspect, disposed on the carrier; and

and the antenna is arranged on the carrier and connected with the transmitting and receiving channel and is used for transmitting and receiving radio signals.

In a seventh aspect, a sensor includes:

a transmitting antenna for transmitting a detection signal;

a receiving antenna for receiving echo signals;

the signal processing module is used for acquiring a preset angle set to be searched; obtaining the number N of target objects; performing N-dimensional search on the angle set to be searched based on maximum likelihood estimation; based on the N-dimensional search result, acquiring azimuth angles of all targets; performing N-dimensional search on the angle set to be searched based on maximum likelihood estimation, wherein the N-dimensional search comprises first-stage search and second-stage search; in the first level search, the initial values of the searches are different; the second-level N-dimensional search result is used for acquiring azimuth angles of all targets;

In one embodiment, the signal processing module may be further configured to implement the method for determining the azimuth angle of the object according to the first aspect.

In one embodiment, the sensor is a MIMO sensor.

In one embodiment, the receiving antenna comprises at least two.

In one embodiment, the sensor is a millimeter wave radar chip.

In one embodiment, the millimeter wave radar chip is a AiP chip.

In an eighth aspect, an apparatus, comprises:

an equipment body; and

a radio device as in the sixth aspect described above, or a sensor as in the seventh aspect described above, provided on the apparatus body;

wherein the radio is used for object detection and/or communication.

According to the azimuth determining method, the azimuth determining device, the computer equipment, the storage medium, the integrated circuit, the radio device, the sensor and the equipment of the target object, when each level of N-dimensional search is sequentially carried out on the angle set to be searched based on maximum likelihood estimation, the N-dimensional search of the same level is carried out, and compared with the traditional search adopting a fixed initial position, the initial value of the search of different levels is different, the level search can be effectively prevented from being trapped into the local extremum point search, so that the probability that the global maximum value can be obtained by searching the angle set to be searched by adopting the maximum likelihood estimation is improved.

Drawings

FIG. 1 is a schematic diagram of an application environment of a method of determining a target azimuth in one embodiment;

FIG. 2 is a schematic diagram of another application environment of a method of determining a target azimuth in one embodiment;

FIG. 3 is a flow chart illustrating a method for determining an azimuth angle of a target in one embodiment;

FIG. 4 is a schematic diagram of determining an angular range of a fine search in one embodiment;

FIG. 5 is a schematic diagram of obtaining a plurality of fine search results in one embodiment;

FIG. 6 is a flow diagram of a method of performing at least two levels of N-dimensional searching in one embodiment;

FIG. 7 is a flow diagram of a method of determining a set of search angle vectors for an mth level N-dimensional search in one embodiment;

FIG. 8 is a schematic diagram of an azimuth determining device for an object according to an embodiment;

fig. 9 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The method, the device, the equipment and the storage medium for determining the azimuth angle of the target object aim to solve the problem of overlarge calculated amount of the traditional method. The following will specifically describe the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems by means of examples and with reference to the accompanying drawings. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

Next, an implementation environment related to the azimuth determination method of the target object provided in the embodiment of the present application will be briefly described.

The method for determining the azimuth angle of the target object provided in this embodiment may be applicable to an application environment as shown in fig. 1. In fig. 1, a sensor 100 and a plurality of targets 200 are shown, where double-headed arrows between the sensor 100 and the targets 200 represent detection signals and echo signals, the sensor 100 includes a transmitting antenna for transmitting the detection signals, a receiving antenna for receiving the echo signals reflected by the targets 200, and a signal processing module for performing signal processing operations such as filtering, down-conversion, analog-to-digital conversion (ADC), sampling (Samp), two-dimensional fourier transform (2D-FFT), constant False Alarm Rate (CFAR), direction of arrival (DOA), and so on the echo signals, so as to obtain radial distance between the targets 200 and the sensors 100, and current speed, azimuth, and other parameters of the targets 200 relative to the sensor 100. Optionally, the signal processing module may be further configured to implement the method for determining the azimuth angle of the target object provided in the embodiments of the present application.

Alternatively, the sensor 100 may be a MIMO sensor.

Alternatively, the sensor 100 may have at least two receiving antennas, that is, the sensor 100 may be a one-to-multiple-transmit or multiple-to-multiple-receive sensor 100, and the distance between the transmitting antennas may be the same or different, which is not limited in the embodiment of the present application.

Alternatively, the sensor 100 may include a millimeter wave radar chip; for example, the millimeter wave radar chip may be a AiP chip.

In an alternative implementation manner, the method for determining the azimuth angle of the target object provided in this embodiment may be applied to the integrated circuit 201 shown in fig. 2, where the integrated circuit 201 includes a signal transceiver channel 2011 for transmitting radio signals and receiving echo signals; an analog-to-digital circuit module 2012 for performing analog-to-digital conversion on the echo information to generate a digital signal; and a digital signal processing module 2013, configured to implement the method for determining the azimuth angle of the target object provided in the embodiments of the present application. Alternatively, the radio signal may be a millimeter wave signal.

Specifically, the integrated circuit may further include other digital circuits, a digital function module and an operation control device, where each type of digital circuit is a basic structure of the integrated circuit, different digital circuits may implement different functions of the integrated circuit, the digital function module is used to detect whether each digital circuit works normally, the operation control device may perform unified configuration management on the digital function module, a digital controller in the operation control device may send a control signal for performing function detection to the digital function module through a digital control interface, the configuration module stores configuration information and state information, the configuration information may be obtained from the outside, the state machine is used to control a workflow of the integrated circuit, the state machine may read the configuration information stored in the configuration module, and generate a corresponding control signal to the control digital controller to output to the digital function module so as to implement control of the digital function module to detect each digital circuit.

The integrated circuit can adopt a unified digital controller to be connected with the digital function module of the system on chip through the digital control interface, and then the configuration module and the state machine are used for realizing unified configuration management of the running state of the digital function module of the system on chip, so that the running control efficiency of the system on chip in the integrated circuit is improved.

Alternatively, in one embodiment, the integrated circuit may be a millimeter wave radar chip, and the radio signal may be a millimeter wave signal. The kind of digital functional modules in the integrated circuit can be determined according to the actual requirements. For example, in a millimeter wave radar chip, the digital function module may be a power detector or the like, which may be used to detect whether the voltage value of the antenna power amplifier is abnormal, and the operation control device may control the operation of the power detector.

In an alternative implementation manner, the method for determining the azimuth angle of the target object provided in this embodiment may be applied to a radio device, where the radio device includes: a carrier; the integrated circuit of the above embodiment, the integrated circuit being disposed on a carrier; the antenna is arranged on the carrier; the integrated circuit is connected with the antenna through a first transmission line and is used for receiving and transmitting radio signals. The carrier may be a printed circuit board PCB, and the first transmission line may be a PCB trace.

In an alternative implementation, the present application further provides an apparatus, including: an equipment body; and the radio device of the above embodiment, or the sensor of the above embodiment, provided on the apparatus body; wherein the radio is used for object detection and/or communication.

Specifically, in one embodiment of the present application, the radio device may be disposed outside the apparatus body, in another embodiment of the present application, the radio device may also be disposed inside the apparatus body, and in other embodiments of the present application, the radio device may also be disposed partially inside the apparatus body, and partially outside the apparatus body. The present application is not limited thereto, and is specific to the case. It should be noted that the radio device may perform functions such as object detection and communication by transmitting and receiving signals.

In an alternative embodiment, the device body may be an intelligent transportation device (such as an automobile, a bicycle, a motorcycle, a ship, a subway, a train, etc.), a security device (such as a camera), an intelligent wearable device (such as a bracelet, glasses, etc.), an intelligent home device (such as a television, an air conditioner, an intelligent lamp, etc.), various communication devices (such as a mobile phone, a tablet computer, etc.), etc., and may also be various instruments for detecting vital sign parameters and various devices carrying the instruments, such as a barrier gate, an intelligent traffic indicator, an intelligent sign, a traffic camera, various industrial manipulators (or robots), etc. The radio device may be a radio device described in any embodiment of the present application, and the structure and working principle of the radio device are described in detail in the above embodiments, which are not described in detail herein.

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments.

Referring to fig. 3, fig. 3 is a flow chart illustrating a method for determining an azimuth angle of a target object according to an embodiment. The method comprises the following steps:

step 301, obtaining a preset angle set to be searched.

The set of angles to be searched may include a plurality of angles to be searched.

In an alternative implementation, the set of angles to be searched is set to include a plurality of preset angles to be searched distributed according to the equal angle difference value. Correspondingly, the interval value of each level of N-dimensional search can be adaptively set according to the equal angle difference, and can be specifically set and adjusted according to actual requirements.

In another alternative implementation, the set of angles to be searched includes a plurality of preset angles to be searched distributed according to the equal function difference. The number of the preset angles to be searched is greater than N, and N is an integer greater than or equal to 2.

For example, the set of angles to be searched in the embodiments of the present application may be defined as:

θ _set ＝{arcsin(sinStart+sinStep·n)|n＝0,1,2,……θ _num-1 }

Wherein θ _set Represents the angle set to be searched, theta _num Representing the number of angles to be searched, sinStart represents the starting sine value of the angles to be searched, sinStep represents the search step of the angles to be searched over the sine domain.

In this embodiment of the present application, a function corresponding to a preset angle to be searched may be represented by f (θ), where a relationship as shown in formula (1) exists between adjacent preset angles to be searched:

f(θ _i )-f(θ _i+1 )＝f(θ _i+1 )-f(θ _i+2 ) Equation (1).

Based on the formula (1), assuming that the difference of functions of any two adjacent preset angles to be searched is 0.1, and taking 0 degree as the initial angle to be searched, equations f (0) -f (theta) can be obtained _i+1 ) =0.1, based on which θ can be calculated _i+1 Then, based on f (θ _i+1 )-f(θ _i+2 ) Calculated θ=0.1 _i+2 And the like, other preset angles to be searched can be obtained through calculation in sequence. The radar may determine a set of angles to be searched according to the plurality of preset angles to be searched, and store the set of angles to be searched into the memory. When the radar needs to determine the azimuth angle of the target object, the radar can acquire a preset angle set to be searched from a memory.

It should be noted that, the difference value of the functions of any two adjacent preset angles to be searched may be set according to the requirement, and in this embodiment of the present application, the magnitude of the difference value of the functions of any two adjacent preset angles to be searched is not limited.

Alternatively, each function difference may be an equal sine function difference.

In this implementation manner, the set of angles to be searched includes a plurality of preset angles to be searched distributed according to the equal function difference, that is, the interval value representing each level of N-dimensional search is also adaptively set according to the equal function difference, and the number of the plurality of preset angles to be searched is greater than N, so as to reduce the iterative operand of the maximum likelihood estimation process.

Step 302, the number N of target objects is obtained.

In this embodiment of the present application, the target object is an object for radar searching, and the number N of target objects may be determined by the radar based on echo signals reflected by the target object.

Step 303, sequentially performing at least two-stage N-dimensional search on the angle set to be searched based on the maximum likelihood estimation.

In an alternative implementation, in at least two levels of N-dimensional search, when multiple searches are performed for any one level of N-dimensional search, the start values of at least two searches are different.

That is, in performing N-dimensional searches at each level, there are at least two different initial values of the searches among the multiple searches for N-dimensional searches at any level, so as to further improve the probability that the global maximum can be obtained by searching the angle set to be searched using maximum likelihood estimation.

In another alternative implementation, at least one level of N-dimensional search exists in at least two levels of N-dimensional searches, and when multiple searches are performed for the same level of N-dimensional search in the at least one level of N-dimensional search, the start values of the multiple searches are different.

That is, for each level of N-dimensional search, the start value of each search is different among a plurality of searches for performing the at least one level of N-dimensional search. The implementation method can further improve the probability that the global maximum value can be obtained by searching the angle set to be searched by adopting maximum likelihood estimation.

In another alternative implementation, in at least two levels of N-dimensional search, when multiple searches are performed for the first level of N-dimensional search, the start values of the respective searches are different. The implementation way can ensure that the global maximum value can be obtained by searching the angle set to be searched by adopting maximum likelihood estimation.

For example, at least two levels of N-dimensional searches include a first level of N-dimensional search (e.g., coarse search) and a second level of N-dimensional search (e.g., fine search) performed sequentially, and when multiple searches are performed for the first level of N-dimensional search, since initial values of the searches are different, it is ensured that a global maximum value can be obtained by searching an angle set to be searched using maximum likelihood estimation.

Meanwhile, for the second-stage N-dimensional search, the conventional fixed initial value can be adopted for each search so as to be effectively compatible with the conventional architecture, algorithm and the like, and different initial values can be adopted for different searches so as to further ensure that the maximum likelihood estimation is adopted for searching the angle set to be searched to obtain the global maximum value.

In addition, the same or different initial value rules can be adopted among different levels of N-dimensional searches, so long as the existence of the difference of initial values among different times of searches of the same level is ensured in each level of N-dimensional searches, and the specific initial value rules can be adaptively set and adjusted according to actual requirements on the premise of not influencing normal implementation of maximum likelihood estimation.

In another alternative implementation, multiple searches are performed with the same interval value for the same level of N-dimensional searches. The method can ensure that global maximum can be obtained by searching the angle set to be searched by adopting maximum likelihood estimation.

Step 304, based on the result of the last-stage N-dimensional search, the azimuth angle of each target is obtained.

In this embodiment of the present application, after the N-dimensional search result is obtained, the radar may determine, as the direction angles of the N targets, a combination corresponding to the largest search result among the N-dimensional search results.

Alternatively, after the N-dimensional search result is obtained, the radar may determine a combination corresponding to the smallest search result among the N-dimensional search results as the direction angles of the N targets.

Optionally, after obtaining the N-dimensional search result, the radar may determine, as the direction angles of the N targets, a combination corresponding to a search result greater than a preset threshold or less than a preset threshold among the N-dimensional search results.

Next, a process of sequentially performing at least two-stage N-dimensional search on an angle set to be searched based on maximum likelihood estimation will be described, and the technical process includes the following steps:

in this embodiment, sequentially performing at least two levels of N-dimensional searches on the angle set to be searched based on the maximum likelihood estimation may refer to performing first a coarse search on the angle set to be searched based on the maximum likelihood estimation and then performing a fine search on the basis of the coarse search, where the coarse search may include multiple coarse searches, and the fine search is a search performed based on the result of the coarse search, and details are described below.

The following describes the course of the rough search, and in the embodiment of the present application, the set of angles to be searched may be represented as { θ } ₀ ,θ ₁ ,θ ₂ ,θ ₃ ,...,θ _n When coarse searching is carried out, selecting a plurality of angles to be searched from the angles to be searched set according to a preset rule to form a coarse searching initial set { theta } ₀ ,θ _step ,θ _2step ,...,θ _{i step} ,...,θ _{k step} Step represents the above-mentioned angle step in the preset set of angles to be searched.For example, step takes a value of 3, then the initial set of coarse searches may be referred to as { θ } ₀ ,θ ₃ ,θ ₆ ,...,θ _3i ,...,θ _3k Then changing the initial value of the initial set of the rough search to obtain a rough search angle set { theta } _0+start ,θ _step+start ,θ _2step+start ,...,θ _{i step+start} ,...,θ _{k step+start} Each time of the rough search, the start search position of each time of the rough search is not fixed by changing the size of the start. Wherein start is an angular increment which is independently generated according to a fixed rule before each coarse search is performed, and the angular increment can be in the range of [0,1, …, step/2 ]]。

It should be noted that, when each coarse search is performed, the initial set of the coarse search in each coarse search may be different by changing the value of step, and the initial search position of each coarse search may be not fixed based on the different initial set of the coarse search.

After the rough search angle set is determined, selecting N angles to be searched from the rough search angle set according to the number N of the target objects as a rough search vector, and obtaining a plurality of different rough search vectors. For example, if the number of objects is 2, the coarse search vector may be expressed as { θ } _i ,θ _j }。

The coarse search vector may then be input into a pre-set search model. The search model may be used to calculate from different coarse search vectors entered, resulting in a coarse search result for each coarse search vector. The calculation of the search model aims at finding the coarse search vector that maximizes the search model globally.

The expression of the search model may be:wherein θ= [ θ ] ₀ ,θ ₁ ,……θ _n-1 ]Representing a set of angles to be searched, x ^H A(A ^H A) ^-1 A ^H x is a cost function, x= [ x ] ₀ ,x ₁ ,……,x _ant-1 ] ^T Echo signals received by the receiving antenna; a= [ a ](θ ₀ ),a(θ ₁ ),……a(θ _n-1 )]The matrix is composed of N (namely 2) preset guide vectors corresponding to the angles to be searched in the combination; a=x ^H a(θ _j )；b＝x ^H a(θ _k ) The method comprises the steps of carrying out a first treatment on the surface of the c=ant is the number of receiving antennas; d is an inner product value determined based on a preset function difference value. />Representing the angle theta _i Corresponding steering vectors, a (θ _k ) Representing the angle theta _k Corresponding steering vector, d _j The ratio of the coordinates of the j-th receiving antenna with respect to the null of the antenna array to the signal wavelength lambda is shown.

Alternatively, the expression of the search model may also beWherein θ= [ θ ] ₀ ,θ ₁ ,……θ _n-1 ]Representing a set of angles to be searched, x ^H A(A ^H A) ^-1 A ^H x is a cost function, x= [ x ] ₀ ,x ₁ ,……,x _ant-1 ] ^T Echo signals received by the receiving antenna; a= [ a (θ) ₀ ),a(θ ₁ ),……a(θ _n-1 )]The matrix is composed of N (namely 2) preset guide vectors corresponding to the angles to be searched in the combination; a=x ^H a(θ _j )；b＝x ^H a(θ _k ) The method comprises the steps of carrying out a first treatment on the surface of the c=ant is the number of receiving antennas; d is an inner product value determined based on a preset function difference value. />Representing the angle theta _i Corresponding steering vectors, a (θ _k ) Representing the angle theta _k Corresponding steering vector, d _j The ratio of the coordinates of the j-th receiving antenna with respect to the null of the antenna array to the signal wavelength lambda is shown.

In this embodiment of the present application, the radar may determine a coarse search vector that meets a preset condition from the coarse search results of each coarse search vector output by the search model, where the preset condition may be a maximum value in the coarse search results of each coarse search vector, or may be a minimum value in the coarse search results of each coarse search vector, and further, the preset condition may also be a coarse search result that is greater than a preset threshold value, or is less than a preset threshold value in the coarse search results of each coarse search vector.

In this embodiment of the present application, for each coarse search, after the determined coarse search vector meeting the preset condition, the fine search may be performed based on the coarse search vector meeting the preset condition. The process of the detail search is described in detail below. For convenience of description, the rough search vector satisfying the preset condition is determined as the target search angle vector as follows.

In the embodiment of the application, the fine search angle set can be determined according to the target search angle vector. Alternatively, as shown in fig. 4, an angle range corresponding to each angle may be determined based on a preset threshold value with each angle in the target search angle vector as a center point, and a range of angle 1 and a range of angle 2 are exemplarily shown in fig. 4. A fine search angle set is determined based on all angles in an angle range to which a plurality of angles in the target search angle vector respectively correspond.

Optionally, for an angle range corresponding to each angle in the target search angle vector, a plurality of angles to be searched may be determined from the angle range according to the equal angle difference. Wherein the equiangular difference may be referred to as disclosed in step 301.

Optionally, for an angle range corresponding to each angle in the target search angle vector, a plurality of angles to be searched may be determined from the angle range according to the equal function difference. Wherein the isofunctional difference can be found in reference to step 301

Then, a plurality of angles to be searched determined from the angle range corresponding to each angle in the target search angle vector are combined to obtain a fine search angle initial set.

After the initial set of fine search angles is obtained, a process of fine search is explained below.

For example, a fine search angle initial setIs combined to { theta ] ₀ ,θ ₁ ,θ ₂ ,θ ₃ ,...,θ _n When fine searching is carried out, selecting some angles to be searched from the initial set of fine searching angles according to a preset rule to form the initial set of fine searching { theta } ₀ ,θ _step ,θ _2step ,...,θ _{i step} ,...,θ _{k step} And the value of step can be different in different times of fine search. For example, step takes a value of 5, then the fine search initial set may refer to { θ } ₀ ,θ ₅ ,θ ₁₀ ,...,θ _5i ,...,θ _5k }. Then changing the initial value of the initial set of the thin search to obtain a fine search angle set { theta } _0+start ,θ _step+start ,θ _2step+start ,...,θ _{i step+start} ,...,θ _{k step+start} }. When the fine search is performed for different times, the value of the start can be different, and the initial search position of each fine search is not fixed by changing the values of the step and the start.

After the fine search angle set is determined, selecting N angles to be searched from the fine search angle set according to the number N of the target objects as one fine search vector, and obtaining a plurality of different fine search vectors. For example, if the number of objects is 2, the fine search vector may be expressed as { θ } _h ,θ _k }。

The fine search vector may then be input into a pre-set search model. The search model may be used to calculate from different fine search vectors entered, resulting in fine search results for each fine search vector. The calculation of the search model aims at finding the fine search vector that maximizes the search model globally. Wherein the expression of the search model for fine search and the search model for coarse search may be the same.

In this embodiment of the present application, the radar may determine a fine search vector that meets a preset condition from the fine search results of each fine search vector output by the search model, where the preset condition may be a maximum value in the fine search results of each fine search vector, or may be a minimum value in the fine search results of each fine search vector, and further, the preset condition may also be a fine search result that is greater than a preset threshold value, or is less than a preset threshold value in the fine search results of each fine search vector.

As shown in fig. 5, when searching is performed, each coarse search may obtain a target search angle vector, and for each target search angle vector, multiple fine searches may be performed, and each fine search may also obtain a fine search result meeting a preset condition, so that a situation may occur in which multiple fine search results are finally obtained as shown in a frame in a dashed line frame in fig. 5. For the plurality of fine search results, in the embodiment of the present application, the fine search result satisfying the preset condition may be determined from the plurality of fine search results, and then the angle in the fine search vector corresponding to the fine search result satisfying the preset condition is determined as the azimuth angle of the target object.

In another alternative implementation, as shown in fig. 6, the technical process of sequentially performing at least two levels of N-dimensional search on the set of angles to be searched based on maximum likelihood estimation includes the following steps:

step 601, for an mth level N-dimensional search of at least two levels of N-dimensional searches, determining a set of search angle vectors for the mth level N-dimensional search according to target search angle vectors for the mth-1 th level N-dimensional search.

The m-th level N-dimensional search angle vector set comprises a plurality of search angle vectors, wherein each search angle vector comprises N angles; m is an integer greater than or equal to 1.

In this embodiment, for the first-stage N-dimensional search of the at least two-stage N-dimensional search, the search angle vector set of the first-stage N-dimensional search may be determined according to the preset set of angles to be searched.

For example, the preset angle set to be searched is { θ } ₀ ,θ ₁ ,θ ₂ ,θ ₃ ,...,θ _n The first level N-dimensional searching initial set { theta } can be formed by selecting some angles to be searched from the preset angles to be searched according to preset rules ₀ ,θ _step ,θ _2step ,...,θ _{i step} ,...,θ _{k step} Then changing the initial value of the first level N-dimensional search initial set to obtain a first level N-dimensional search angle set { theta } _0+start ,θ _step+start ,θ _2step+start ,...,θ _{i step+start} ,...,θ _{k step+start} }。

In the process of determining the search angle vector sets of the N-dimensional searches of different levels, the initial search position of the N-dimensional search angle sets of each level can be not fixed by changing the values of step and start.

After the first-stage N-dimensional search angle set is determined, N angles to be searched are selected from the first-stage N-dimensional search angle set to serve as one search angle vector according to the number N of the target objects, and a plurality of different search angle vectors are obtained. For example, if the number of objects is 2, the search angle vector may be expressed as { θ } _i ,θ _j }. The plurality of different search angle vectors are grouped into a set of search angle vectors for a first level N-dimensional search.

And respectively inputting the search angle vectors contained in the search angle vector set of the first-stage N-dimensional search into a preset search model, and obtaining an output result corresponding to each search angle vector output by the model.

The search model may refer to the search model disclosed in the above embodiment.

In this embodiment of the present application, the radar may determine an output result according with a preset condition from output results of each search angle vector output by the search model, where the preset condition may be a maximum value or a minimum value in output results of each search angle vector, and further, the preset condition may also be an output result greater than or less than a preset threshold in output results of each search angle vector. And then determining the search angle vector corresponding to the output result meeting the preset condition as the target search angle vector of the first-stage N-dimensional search.

The following describes a process of determining a set of search angle vectors for an m-th level N-dimensional search from target search angle vectors for the m-1-th level N-dimensional search, as shown in fig. 7, including the steps of:

step 701, determining a candidate angle range according to a target search angle vector of the m-1 level N-dimensional search.

After the target search angle vector of the first-stage N-dimensional search is obtained, each angle in the target search angle vector of the first-stage N-dimensional search can be taken as a center point, and a candidate angle range corresponding to each angle can be determined based on a preset threshold. The candidate angle range for angle 1 and the candidate angle range for angle 2 are exemplarily shown in fig. 4. And determining a search angle vector set of the second-stage N-dimensional search based on all angles in the candidate angle range respectively corresponding to the plurality of angles in the target search angle vector.

Step 702, determining a plurality of angles to be searched distributed according to the equal function difference value from the candidate angle range.

Optionally, for a candidate angle range corresponding to each angle in the target search angle vector, a plurality of angles to be searched may be determined from the candidate angle range according to the equal angle difference. Or a plurality of angles to be searched can be determined from the candidate angle range according to the equal function difference value.

Step 703, determining a search angle vector set of the m-th level N-dimensional search according to the plurality of angles to be searched.

In this embodiment of the present application, the plurality of angles to be searched may be combined to obtain the second-stage N-dimensional search initial set.

Then, when the second-stage N-dimensional search is performed, the initial value of the second-stage N-dimensional search initial set can be changed to obtain a second-stage N-dimensional search angle set { theta } _0+start ,θ _1+start ,θ _2+start ,θ _3+start ,...,θ _n+start }. When the second-stage N-dimensional search is performed for different times, the initial search position of each stage N-dimensional search angle set is not fixed by changing the value of the start.

And in the second-stage N-dimensional search angle set, N angles to be searched are selected from the second-stage N-dimensional search angle set as one search angle vector according to the number N of the target objects, so that a plurality of different search angle vectors are obtained. For example, if the number of objects is 3, the search angle vector may be expressed as { θ } _m ,θ _l ,θ _n }。The plurality of different search angle vectors are grouped into a set of search angle vectors for a second level N-dimensional search.

The target search angle vector of the m-1 th order N-dimensional search can be obtained based on the same principle as described above.

Step 602, inputting the search angle vector set of the m-th level N-dimensional search into a preset search model to obtain an output result of the m-th level N-dimensional search.

In the following, taking the m-th level as the 2-th level as an example, the search angle vectors contained in the search angle vector set of the second-level N-dimensional search are respectively input into a preset search model, so that the output result of each search angle vector contained in the search angle vector set of the second-level N-dimensional search output by the search model can be obtained.

And 603, determining a target search angle vector of the m-th level N-dimensional search according to the output result of the m-th level N-dimensional search.

The radar can determine an output result meeting a preset condition from output results of each search angle vector contained in a search angle vector set of the second-stage N-dimensional search output by the search model, and then determine a search angle vector corresponding to the output result meeting the preset condition as a target search angle vector of the second-stage N-dimensional search.

Based on the disclosure of the above steps 601-603, the process is repeated until the multi-level N-dimensional search is performed.

In this embodiment of the present application, if the mth-level N-dimensional search is the last-level N-dimensional search of the at least two-level N-dimensional searches, the output result of each search angle vector included in the search angle vector set of the mth-level N-dimensional search output by the search model is used as the result of the last-level N-dimensional search.

In the embodiment of the application, N-dimensional search is performed for a plurality of times in a cyclic manner, and the initial search position of the angle set is not fixed in N-dimensional search of each level by changing the step and/or start value during N-dimensional search. Compared with the traditional search adopting a fixed initial position, the method can effectively avoid the stage of search from sinking into local extremum point search, so as to improve the probability that the global maximum value can be obtained by searching the angle set to be searched by adopting maximum likelihood estimation.

It should be understood that, although the steps in the flowcharts of fig. 3 to 7 are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps of fig. 3-7 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps or stages of other steps.

Fig. 8 is a schematic structural diagram of an azimuth determining device for a target object provided in an embodiment, and as shown in fig. 8, an azimuth determining device 800 for a target object includes: a first acquisition module 801, a second acquisition module 802, a search module 803 and an azimuth determination module 803, wherein:

a first obtaining module 801, configured to obtain a preset set of angles to be searched;

a second obtaining module 802, configured to obtain the number N of the objects;

a searching module 803, configured to sequentially perform at least two-stage N-dimensional searching on the angle set to be searched based on the maximum likelihood estimation; and

an azimuth determining module 804, configured to obtain azimuth angles of the targets based on the result of the last-stage N-dimensional search;

In one embodiment, the search module 803 is specifically configured to: in at least two-stage N-dimensional search, when a plurality of searches are performed for any one of the two-stage N-dimensional search, the start values of at least two searches are different.

In one embodiment, the search module 803 is specifically configured to: at least one level of N-dimensional search exists in at least two levels of N-dimensional searches, and when the same level of N-dimensional search in the at least one level of N-dimensional search is searched for a plurality of times, the initial values of the searches are different.

In one embodiment, the search module 803 is specifically configured to: in at least two-stage N-dimensional search, when a plurality of searches are performed with respect to the first-stage N-dimensional search, the start values of the respective searches are different.

In one embodiment, the search module 803 is specifically configured to: and aiming at the N-dimensional search of the same level, carrying out multiple searches by adopting the same interval value.

In one embodiment, the first obtaining module 801 is specifically configured to: the angle set to be searched comprises a plurality of preset angles to be searched distributed according to the equal function difference value, and the number of the preset angles to be searched is larger than N.

In one embodiment, the search module 803 is specifically configured to:

For a specific definition of the azimuth determining device of an object, reference may be made to the definition of the azimuth determining method of the object hereinabove, and the description thereof will not be repeated here. The modules in the azimuth determining device of the object may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of determining an azimuth angle of a target object. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:

acquiring a preset angle set to be searched; obtaining the number N of target objects; sequentially performing at least two-stage N-dimensional search on the angle set to be searched based on maximum likelihood estimation; based on the result of the last-stage N-dimensional search, acquiring azimuth angles of all targets; wherein, there is at least one level N dimension searching in at least two levels of N dimension searching, when searching for the same level N dimension searching in the at least one level N dimension searching many times, the initial values of at least two times of searching are different; n is an integer greater than or equal to 2.

In one embodiment, the processor when executing the computer program further performs the steps of: in at least two-stage N-dimensional search, when a plurality of searches are performed for any one of the two-stage N-dimensional search, the start values of at least two searches are different.

In one embodiment, the processor when executing the computer program further performs the steps of: at least one level of N-dimensional search exists in at least two levels of N-dimensional searches, and when the same level of N-dimensional search in the at least one level of N-dimensional search is searched for a plurality of times, the initial values of the searches are different.

In one embodiment, the processor when executing the computer program further performs the steps of: in at least two-stage N-dimensional search, when a plurality of searches are performed with respect to the first-stage N-dimensional search, the start values of the respective searches are different.

In one embodiment, the processor when executing the computer program further performs the steps of: and aiming at the N-dimensional search of the same level, carrying out multiple searches by adopting the same interval value.

In one embodiment, the processor when executing the computer program further performs the steps of: the angle set to be searched comprises a plurality of preset angles to be searched distributed according to the equal function difference value, and the number of the preset angles to be searched is larger than N.

In one embodiment, the processor when executing the computer program further performs the steps of: for an mth level N-dimensional search in at least two levels of N-dimensional searches, determining a search angle vector set of the mth level N-dimensional search according to target search angle vectors of the mth-1 level N-dimensional search, wherein the search angle vector set of the mth level N-dimensional search comprises a plurality of search angle vectors, and each search angle vector comprises N angles; m is an integer greater than or equal to 1; inputting the search angle vector set of the m-th level N-dimensional search into a preset search model to obtain an output result of the m-th level N-dimensional search; determining a target search angle vector of the m-th level N-dimensional search according to the output result of the m-th level N-dimensional search; if the m-th level N-dimensional search is the last level N-dimensional search of at least two levels of N-dimensional searches, taking the output result of the m-th level N-dimensional search as the result of the last level N-dimensional search; if the m-th level N-dimensional search is the first level N-dimensional search of at least two levels of N-dimensional searches, determining a search angle vector set of the m-th level N-dimensional search according to a preset angle set to be searched.

In one embodiment, the processor when executing the computer program further performs the steps of: determining a candidate angle range according to a target search angle vector of the m-1 level N-dimensional search; determining a plurality of angles to be searched distributed according to the equal function difference value from the candidate angle range; and determining a search angle vector set of the m-th level N-dimensional search according to the plurality of angles to be searched.

The computer device provided in this embodiment has similar implementation principles and technical effects to those of the above method embodiment, and will not be described herein.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by a processor performs the steps of: in at least two-stage N-dimensional search, when a plurality of searches are performed for any one of the two-stage N-dimensional search, the start values of at least two searches are different.

In one embodiment, the computer program when executed by a processor performs the steps of: at least one level of N-dimensional search exists in at least two levels of N-dimensional searches, and when the same level of N-dimensional search in the at least one level of N-dimensional search is searched for a plurality of times, the initial values of the searches are different.

In one embodiment, the computer program when executed by a processor performs the steps of: in at least two-stage N-dimensional search, when a plurality of searches are performed with respect to the first-stage N-dimensional search, the start values of the respective searches are different.

In one embodiment, the computer program when executed by a processor performs the steps of: and aiming at the N-dimensional search of the same level, carrying out multiple searches by adopting the same interval value.

In one embodiment, the computer program when executed by a processor performs the steps of: the angle set to be searched comprises a plurality of preset angles to be searched distributed according to the equal function difference value, and the number of the preset angles to be searched is larger than N.

In one embodiment, the computer program when executed by a processor performs the steps of: for an mth level N-dimensional search in at least two levels of N-dimensional searches, determining a search angle vector set of the mth level N-dimensional search according to target search angle vectors of the mth-1 level N-dimensional search, wherein the search angle vector set of the mth level N-dimensional search comprises a plurality of search angle vectors, and each search angle vector comprises N angles; m is an integer greater than or equal to 1; inputting the search angle vector set of the m-th level N-dimensional search into a preset search model to obtain an output result of the m-th level N-dimensional search; determining a target search angle vector of the m-th level N-dimensional search according to the output result of the m-th level N-dimensional search; if the m-th level N-dimensional search is the last level N-dimensional search of at least two levels of N-dimensional searches, taking the output result of the m-th level N-dimensional search as the result of the last level N-dimensional search; if the m-th level N-dimensional search is the first level N-dimensional search of at least two levels of N-dimensional searches, determining a search angle vector set of the m-th level N-dimensional search according to a preset angle set to be searched.

In one embodiment, the computer program when executed by a processor performs the steps of: determining a candidate angle range according to a target search angle vector of the m-1 level N-dimensional search; determining a plurality of angles to be searched distributed according to the equal function difference value from the candidate angle range; and determining a search angle vector set of the m-th level N-dimensional search according to the plurality of angles to be searched.

The computer readable storage medium provided in this embodiment has similar principles and technical effects to those of the above method embodiment, and will not be described herein.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A method of determining azimuth of a target, the method comprising:

acquiring a preset angle set to be searched;

obtaining the number N of target objects;

Wherein, at least one level of N-dimensional search exists in the at least two levels of N-dimensional searches, and when the same level of N-dimensional search in the at least one level of N-dimensional search is searched for a plurality of times, the initial values of at least two times of searches are different; n is an integer greater than or equal to 2.

2. The method according to claim 1, wherein in the at least two-stage N-dimensional search, when a plurality of searches are performed for any one stage N-dimensional search, start values of at least two searches are different.

3. The method according to claim 1, wherein there is at least one level of N-dimensional search among the at least two levels of N-dimensional searches, and start values of the respective searches are different when the searches are performed for the same level of N-dimensional search among the at least one level of N-dimensional search.

4. A method according to claim 3, characterized in that in the at least two-stage N-dimensional search, when a plurality of searches are performed for the first-stage N-dimensional search, the start values of the respective searches are different.

5. The method as recited in claim 1, further comprising:

and aiming at the N-dimensional search of the same level, adopting the same interval value to perform the multiple searches.

6. The method according to any one of claims 1-5, wherein the set of angles to be searched comprises a plurality of preset angles to be searched distributed according to an equal function difference, and the number of the preset angles to be searched is greater than N.

7. The method of claim 1, wherein the sequentially performing at least two levels of N-dimensional search on the set of angles to be searched based on maximum likelihood estimation comprises:

for an mth level N-dimensional search of the at least two levels N-dimensional searches, determining a set of search angle vectors of the mth level N-dimensional search according to target search angle vectors of the mth-1 level N-dimensional search, the set of search angle vectors of the mth level N-dimensional search including a plurality of search angle vectors, each of the search angle vectors including N angles; m is an integer greater than or equal to 2;

if the mth level N-dimensional search is the last level N-dimensional search of the at least two levels N-dimensional searches, taking an output result of the mth level N-dimensional search as a result of the last level N-dimensional search; and if the m-th level N-dimensional search is the first level N-dimensional search of the at least two levels of N-dimensional searches, determining a search angle vector set of the m-th level N-dimensional search according to the preset to-be-searched angle set.

8. The method of claim 7, wherein the determining the set of search angle vectors for the m-th level N-dimensional search from the target search angle vectors for the m-1-th level N-dimensional search comprises:

determining a candidate angle range according to the target search angle vector of the m-1 level N-dimensional search;

9. An azimuth determining device for an object, the device comprising:

the searching module is used for sequentially carrying out at least two-stage N-dimensional searching on the angle set to be searched based on maximum likelihood estimation; and

10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-8 when the computer program is executed.

11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-8.

12. An integrated circuit for determining an azimuth of a target, comprising:

the method comprises the steps of carrying out N-dimensional search on an angle set to be searched based on maximum likelihood estimation, wherein the N-dimensional search comprises a first-stage N-dimensional search and a second-stage N-dimensional search; in the first level N-dimensional search, the initial values of the searches are different; and the second-stage N-dimensional search result is used for acquiring the azimuth angle of each target object.

13. The integrated circuit of claim 12, wherein the radio signal is a millimeter wave signal; and/or

The set of angles to be searched comprises a plurality of preset angles to be searched distributed according to the equal function difference value, N is an integer greater than or equal to 2, and the number of the preset angles to be searched is greater than N.

14. A radio device for determining an azimuth of a target, comprising:

a carrier;

an integrated circuit as claimed in claim 12 or 13, disposed on a carrier; and

15. A sensor for determining the azimuth of a target, comprising:

a transmitting antenna for transmitting a detection signal;

a receiving antenna for receiving echo signals; and

the signal processing module is used for acquiring a preset angle set to be searched; obtaining the number N of target objects; performing N-dimensional search on the angle set to be searched based on maximum likelihood estimation; based on the N-dimensional search result, acquiring azimuth angles of all targets;

the method comprises the steps of carrying out N-dimensional search on an angle set to be searched based on maximum likelihood estimation, wherein the N-dimensional search comprises a first-stage N-dimensional search and a second-stage N-dimensional search; in the first level N-dimensional search, the initial values of the searches are different; the second-level N-dimensional search result is used for acquiring azimuth angles of all targets;

16. The sensor of claim 15, wherein the signal processing module is further configured to implement the method of determining the azimuth of the target object of any one of claims 2-8.

17. The sensor of claim 15, wherein the sensor is a MIMO sensor.

18. The sensor of claim 15, wherein the receiving antenna comprises at least two.

19. The sensor of claim 15, wherein the sensor is a millimeter wave radar chip.

20. The sensor of claim 19, wherein the millimeter wave radar chip is a AiP chip.

21. An apparatus for determining an azimuth of a target, comprising:

an equipment body; and

a radio device according to claim 14, or a sensor according to any of claims 15-20, disposed on the device body;

wherein the radio device is used for target detection and/or communication.