A signal quantization method and apparatus for DOA estimation

Abstract

This invention provides a signal quantization method for DOA estimation, comprising: receiving a signal using a mixed-precision quantization array and quantizing the signal; calculating the covariance matrix of the quantized signal and calculating the covariance matrix before quantization according to the type of covariance array elements; and using the MUSIC algorithm to estimate the DOA of the covariance matrix before quantization. By employing mixed-precision quantization technology in the system, the need for using a full-precision ADC is significantly reduced, thereby lowering hardware costs. Compared to the pure 1-bit quantization method, it significantly improves DOA estimation accuracy and target recognition capability, especially under high signal-to-noise ratio conditions, where the mixed-precision quantization method can effectively reduce the impact of quantization noise. This method is not only applicable to DOA estimation but can also be applied to subsequent signal processing tasks, such as target recognition and tracking, enhancing the overall performance of the system.

Description

Technical Field

[0001] This invention belongs to the field of sensing technology, and particularly relates to a signal quantization method and apparatus for DOA estimation. Background Technology

[0002] Direction of Arrival (DOA) estimation is a common information processing technique widely used in wireless communication, acoustic localization, radar, and robot navigation. The most common DOA estimation methods are based on full-precision signals, such as the MUSIC (Multiple Signal Classification) algorithm and the ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm. However, in digital systems, as the quantization precision of full-precision signals increases, hardware costs and power consumption also increase. To address this, researchers have proposed 1-bit quantization techniques, which reduce signal precision to 1 bit using an analog-to-digital converter (ADC), thereby reducing hardware complexity and power consumption.

[0003] While 1-bit quantization significantly reduces hardware costs, it introduces substantial quantization noise, leading to decreased DOA estimation accuracy. Furthermore, 1-bit quantization can also impact the performance of other tasks, such as object recognition. Therefore, despite its advantages in power consumption and cost, 1-bit quantization technology faces significant challenges in terms of performance and accuracy. Summary of the Invention

[0004] This application provides a signal quantization method for DOA estimation, including:

[0005] The signal is received using a mixed-precision quantization array, and the signal is quantized.

[0006] Calculate the covariance matrix of the quantized signal, and calculate the covariance matrix before quantization according to the type of covariance matrix elements;

[0007] The MUSIC algorithm is used to estimate the DOA of the covariance matrix before quantization.

[0008] Furthermore, the mixed-precision quantization matrix includes: at least one full-precision ADC + comparator; the process of receiving the signal using the mixed-precision quantization array and performing quantization on the signal specifically involves:

[0009] The signal is quantized using the full-precision ADC and comparator.

[0010] Furthermore, the calculation of the covariance matrix of the quantized signal is specifically performed by calculating the covariance matrix of all array elements after quantization using the following covariance formula:

[0011]

[0012] Here, Ry is the covariance matrix of all array elements after quantization, and the calculated result has the following structure:

[0013]

[0014] Where, r xixj Let y(t) represent the covariance between the i-th and j-th array elements, and let y(t) represent the received signal vector of the mixed-precision quantized array. H (t) represents the conjugate transpose of the received signal vector of the mixed-precision quantization array.

[0015] Furthermore, the covariance matrix before quantization is calculated according to the type of covariance matrix elements, including:

[0016] Depending on the array element type, we can use r xixj The covariance r before quantization is restored ij And form the covariance matrix of all array elements before quantization.

[0017] For the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is:

[0018] r ij =r xixj

[0019] The covariance between two 1-bit quantized elements is calculated using the following formula:

[0020]

[0021] The covariance between a 1-bit quantized array element and a full-precision array element is calculated using the following formula:

[0022]

[0023] in, and These represent the real and imaginary parts of a complex number, respectively.

[0024] The covariance r of the above three types ij Arrange the array elements in order to obtain the covariance matrix R of all array elements before quantization.

[0025]

[0026] This invention also provides a signal quantization apparatus for DOA estimation, comprising:

[0027] An acquisition module is used to receive signals using a mixed-precision quantization array and to quantize the signals.

[0028] The processing module is used to calculate the covariance matrix of the quantized signal and calculate the covariance matrix before quantization according to the type of covariance matrix elements.

[0029] The execution module is used to perform DOA estimation on the covariance matrix before quantization using the MUSIC algorithm.

[0030] Furthermore, the mixed-precision quantization matrix includes: at least one full-precision ADC + comparator;

[0031] The acquisition module is also used to perform mixed-precision quantization on the signal using the full-precision ADC+ comparator.

[0032] Furthermore,

[0033] The processing module is also used to calculate the covariance matrix of all array elements after quantization using the following covariance formula:

[0034]

[0035] Here, Ry is the covariance matrix of all array elements after quantization, and the calculated result has the following structure:

[0036]

[0037] Where, r xixj Let y(t) represent the covariance between the i-th and j-th array elements, and let y(t) represent the received signal vector of the mixed-precision quantized array. H (t) represents the conjugate transpose of the received signal vector of the mixed-precision quantization array.

[0038] Furthermore, the execution module is also configured to use r according to the array element type. xixj The covariance r before quantization is restored ij And form the covariance matrix of all array elements before quantization, including:

[0039] In the first execution submodule, for the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is:

[0040] r ij =r xixj

[0041] The second execution submodule calculates the covariance before quantization using the following formula for the covariance between two 1-bit quantized array elements:

[0042]

[0043] The third execution submodule calculates the covariance between a 1-bit quantized array element and a full-precision array element using the following formula:

[0044]

[0045] in, and These represent the real and imaginary parts of a complex number, respectively.

[0046] The fourth execution submodule arranges the above three types of covariances in the order of array elements to obtain the covariance matrix R of all array elements before quantization.

[0047]

[0048] The present invention provides a computer device including a memory and a processor, wherein the memory stores computer-readable instructions, and when executed by the processor, the computer-readable instructions cause the processor to perform the steps of the signal quantization method for DOA estimation as described above.

[0049] The present invention provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the signal quantization method for DOA estimation as described above.

[0050] This invention significantly reduces the need for a full-precision ADC by employing mixed-precision quantization technology in the system, thereby lowering hardware costs. Compared to pure 1-bit quantization, this invention significantly improves DOA estimation accuracy and target recognition capability, especially under high signal-to-noise ratio conditions, where mixed-precision quantization effectively reduces the impact of quantization noise. This method is not only applicable to DOA estimation but can also be applied to subsequent signal processing tasks, such as target recognition and tracking, enhancing the overall system performance. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A schematic flowchart of a signal quantization method for DOA estimation provided by the present invention;

[0053] Figure 2 This is a schematic diagram of a mixed-precision quantization array consisting of a full-precision ADC and a comparator, provided by the present invention. Detailed Implementation

[0054] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0055] like Figure 1 As shown, this embodiment of the invention provides a signal quantization method for DOA estimation, comprising:

[0056] S1. Receive the signal using a mixed-precision quantization array and complete the quantization of the signal;

[0057] The mixed-precision quantization matrix includes: at least one full-precision ADC + comparator; the process of receiving the signal using the mixed-precision quantization array and performing quantization on the signal specifically involves:

[0058] The signal is quantized using the full-precision ADC and comparator.

[0059] In this embodiment, the mixed-precision quantization array consists of one or two full-precision ADCs plus multiple comparators (i.e., 1-bit quantized ADCs). Figure 2 In one embodiment shown, the first array element uses a full-precision ADC, while the other array elements use comparators.

[0060] S2. Calculate the covariance matrix of the quantized signal, and calculate the covariance matrix before quantization according to the type of covariance matrix elements.

[0061] This embodiment uses the following covariance formula to calculate the covariance matrix of all array elements after quantization:

[0062]

[0063] R here y The covariance matrix of all array elements after quantization has the following structure:

[0064]

[0065] r xixj (1≤i,j≤M) represents the covariance (i.e., the quantized covariance) between the signals received by the i-th and j-th array elements, where M is the number of sensors, and y(t) represents the received signal vector of the mixed-precision quantized array. H(t) represents the conjugate transpose of the received signal vector of the mixed-precision quantization array. Depending on the element type, we can use this covariance r. xixj The covariance r before quantization is restored ij and using these covariances r ij The covariance matrix of all array elements before quantization is formed, and there are three cases:

[0066] For the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is:

[0067] r ij =r xixj

[0068] The covariance between two 1-bit quantized elements is calculated using the following formula:

[0069]

[0070] The covariance between a 1-bit quantized array element and a full-precision array element is expressed by the following formula.

[0071] Calculate covariance:

[0072]

[0073] in, and Let r represent the real and imaginary parts of a complex number, respectively. Then, let r represent the covariances of the three types mentioned above. ij Arranging the array elements in order yields the covariance matrix of all array elements before quantization, which is R in the following formula.

[0074]

[0075] S3. Use the MUSIC algorithm or other algorithms to estimate the DOA of the recovered quantized covariance matrix.

[0076] In this embodiment, MATLAB's built-in functions are used for calculation.

[0077] This invention is applied to wireless communication, radar and acoustic localization, and robot navigation technologies. For example, in wireless communication, in massive MIMO systems, hybrid precision quantization techniques can reduce hardware costs while improving DOA estimation performance. In radar and acoustic localization, it can be used for target recognition and tracking tasks, improving detection and tracking accuracy. In robot navigation, by improving DOA estimation accuracy, the robot's navigation and environmental awareness capabilities are enhanced.

[0078] This invention significantly reduces the need for a full-precision ADC by employing mixed-precision quantization technology in the system, thereby lowering hardware costs. Compared to pure 1-bit quantization, this invention significantly improves DOA estimation accuracy and target recognition capability, especially under high signal-to-noise ratio conditions, where mixed-precision quantization effectively reduces the impact of quantization noise. This method is not only applicable to DOA estimation but can also be applied to subsequent signal processing tasks, such as target recognition and tracking, enhancing the overall system performance.

[0079] The embodiments of this invention can be applied to the following technical fields: Wireless communication: In massive MIMO systems, hybrid precision quantization technology can reduce hardware costs while improving DOA estimation performance. Radar and acoustic localization: This invention can be used for target recognition and tracking tasks, improving detection and tracking accuracy. Robot navigation: By improving DOA estimation accuracy, the navigation and environmental awareness capabilities of robots are enhanced.

[0080] This invention also provides a signal quantization apparatus for DOA estimation, comprising:

[0081] The acquisition module is used to receive signals using a mixed-precision quantization array and complete the quantization of the signals; the processing module is used to calculate the covariance matrix of the quantized signals and calculate the covariance matrix before quantization according to the type of covariance matrix elements; the execution module is used to perform DOA estimation on the covariance matrix before quantization using the MUSIC algorithm.

[0082] In some embodiments, the mixed-precision quantization matrix includes at least one full-precision ADC+ comparator. In some embodiments, the acquisition module is further configured to perform mixed-precision quantization on the signal using the full-precision ADC+ comparator.

[0083] In some embodiments, the processing module is further configured to calculate the covariance matrix of all elements after quantization using the following covariance formula:

[0084] Ry is the covariance matrix of all elements after quantization, and its calculated result has the following structure:

[0085]

[0086] Where, r xixj Let y(t) represent the covariance between the i-th and j-th array elements, and let y(t) represent the received signal vector of the mixed-precision quantized array. H (t) represents the conjugate transpose of the received signal vector of the mixed-precision quantization array.

[0087] In some embodiments, the execution module is further configured to use r according to the element type. xixjThe covariance r before quantization is restored ij And form the covariance matrix of all array elements before quantization; including:

[0088] In the first execution submodule, for the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is:

[0089] r ij =r xixj

[0090] The second execution submodule calculates the covariance before quantization using the following formula for the covariance between two 1-bit quantized array elements:

[0091]

[0092] The third execution submodule calculates the covariance between a 1-bit quantized array element and a full-precision array element using the following formula:

[0093]

[0094] in, and These represent the real and imaginary parts of a complex number, respectively.

[0095] The fourth execution submodule arranges the above three types of covariances in the order of array elements to obtain the covariance matrix R of all array elements before quantization.

[0096]

[0097] This invention significantly reduces the need for a full-precision ADC by employing mixed-precision quantization technology in the system, thereby lowering hardware costs. Compared to pure 1-bit quantization, this invention significantly improves DOA estimation accuracy and target recognition capability, especially under high signal-to-noise ratio conditions, where mixed-precision quantization effectively reduces the impact of quantization noise. This method is not only applicable to DOA estimation but can also be applied to subsequent signal processing tasks, such as target recognition and tracking, enhancing the overall system performance.

[0098] To address the aforementioned technical problems, this invention also provides a computer device. The computer device includes a processor, a non-volatile storage medium, a memory, and a network interface connected via a system bus. The non-volatile storage medium stores an operating system, a database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, the processor can implement a signal quantization method for DOA estimation. The processor provides computational and control capabilities to support the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to execute a signal quantization method for DOA estimation. The network interface is used for communication with a terminal. In this embodiment, the processor executes the specific content of the acquisition module and the processing module, and the memory stores the program code and various types of data required to execute these modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all sub-modules in the image processing method, and the server can call the server's program code and data to execute the functions of all sub-modules.

[0099] The present invention also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the signal quantization method for DOA estimation described in any of the above embodiments.

[0100] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0101] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0102] The above description is only a partial embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0103] The above content is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A signal quantization method for DOA estimation, characterized in that, include: The signal is received using a mixed-precision quantization array, and the signal is quantized. Calculate the covariance matrix of the quantized signal, and calculate the covariance matrix before quantization according to the type of covariance matrix elements; The MUSIC algorithm is used to estimate the DOA of the covariance matrix before quantization. The mixed-precision quantization array includes: at least one full-precision ADC + comparator; the process of receiving a signal using the mixed-precision quantization array and performing quantization on the signal specifically involves: The signal is quantized using the full-precision ADC+ comparator; The calculation of the covariance matrix of the quantized signal is specifically performed by calculating the covariance matrix of all array elements after quantization using the following covariance formula: Here, Ry is the covariance matrix of all array elements after quantization, and the calculated result has the following structure: in, This represents the covariance between the i-th and j-th array elements. This represents the received signal vector of the mixed-precision quantization array. This represents the conjugate transpose of the received signal vector of the mixed-precision quantization array; Calculate the covariance matrix before quantization according to the type of covariance matrix elements, including: Use according to the array element type The covariance r before quantization ij And form the covariance matrix of all array elements before quantization; For the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is: The covariance between two 1-bit quantized elements is calculated using the following formula: The covariance between a 1-bit quantized array element and a full-precision array element is calculated using the following formula: in, and These represent the real and imaginary parts of a complex number, respectively. Three types of covariance r ij Arrange the array elements in order to obtain the covariance matrix R of all array elements before quantization. 。 2. A signal quantization device for DOA estimation, characterized in that, include: An acquisition module is used to receive signals using a mixed-precision quantization array and to quantize the signals. The processing module is used to calculate the covariance matrix of the quantized signal and calculate the covariance matrix before quantization according to the type of covariance matrix elements. The execution module is used to perform DOA estimation on the covariance matrix before quantization using the MUSIC algorithm; The mixed-precision quantization array includes: at least one full-precision ADC + comparator; The acquisition module is also used to perform mixed-precision quantization on the signal using the full-precision ADC+ comparator; The processing module is also used to calculate the covariance matrix of all array elements after quantization using the following covariance formula: Here, Ry is the covariance matrix of all array elements after quantization, and the calculated result has the following structure: in, This represents the covariance between the i-th and j-th array elements. This represents the received signal vector of the mixed-precision quantization array. This represents the conjugate transpose of the received signal vector of the mixed-precision quantization array; The execution module is also used to, based on the array element type, use The covariance r before quantization ij And form the covariance matrix of all array elements before quantization, including: In the first execution submodule, for the covariance between two full-precision array elements, the covariance before and after quantization is equal, that is: The second execution submodule calculates the covariance before quantization using the following formula for the covariance between two 1-bit quantized array elements: The third execution submodule calculates the covariance between a 1-bit quantized array element and a full-precision array element using the following formula: in, and These represent the real and imaginary parts of a complex number, respectively. The fourth execution submodule will handle the three types of covariance r. ij Arrange the array elements in order to obtain the covariance matrix R of all array elements before quantization. 。 3. A computer device comprising a memory and a processor, the memory storing computer-readable instructions which, when executed by the processor, cause the processor to perform the steps of the signal quantization method for DOA estimation as described in claim 1.

4. A storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the signal quantization method for DOA estimation as described in claim 1.

Images