A geometric quantization digital filtering method and digital filter

Abstract

The embodiment of the present invention discloses a geometric order quantization digital filtering method and a digital filter. The digital filtering method comprises: based on a preset quantization bit number m, quantizing the impulse response coefficient of the digital filter, obtaining the quantization result q(k) of the impulse response of the digital filter, wherein the quantization result q(k) comprises the real coefficient q r (k) and the imaginary coefficient q i (k), the real coefficient q r (k) and the imaginary coefficient q i (k) all include values ​​after exponential operation with base 2, the input signal is calculated based on the quantized digital filter impulse response to obtain the shift calculation result s(k, l) of the input signal, and the shift calculation result is added to obtain the filtering output result. The embodiment of the present invention realizes the convolution calculation of the existing digital filter by replacing the shift calculation with the quantized result after the digital filter impulse response function is transformed, thereby greatly reducing the hardware resources and calculation complexity required for the digital filter.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication and signal processing, and in particular to a geometric order quantization digital filtering method and a digital filter. Background Art

[0002] Filtering is a basic and important technology in signal processing. It is mainly used for signal filtering, detection, and prediction. It is widely used in many fields such as computer networks, big data analysis, instruments, military, industrial control, communications, and aerospace. Digital filters are an algorithm or device composed of digital multipliers, adders, and delay units. They have many outstanding advantages such as high stability, high precision, flexible design, and convenient implementation. They avoid problems such as voltage drift, temperature drift, and noise that analog filters cannot overcome. Due to the development of electronic computer technology and large-scale integrated circuits, digital filters can be implemented by computer software or in real time using large-scale integrated digital hardware.

[0003] For a finite impulse response (FIR) filter, the output y(k) of its operation is the convolution of the input signal x(k) and the impulse response h(k), that is, the input signal x(k) at each moment is multiplied by the attenuation or amplification corresponding to the finite impulse response h(k), and then superimposed together as the output signal. The computational complexity of the FIR filter is determined by the order N of its impulse response. The larger N is, the larger the storage space occupied by the filter is, and the more multipliers, adders, and delay units are required, which poses a great challenge to the real-time calculation of large-scale integrated digital circuits. Summary of the invention

[0004] The embodiment of the present invention provides a geometrically quantized digital filtering method and a digital filter, which can greatly reduce the hardware resources and computational complexity required for the digital filter. The specific technical solution is as follows:

[0005] In a first aspect of the present invention, a geometric order quantization digital filtering method is provided, wherein the digital filtering method comprises: quantizing the impulse response coefficients of the digital filter based on a preset quantization bit number m, and obtaining the quantization result of the impulse response of the digital filter. , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient All include the values ​​after exponential operation with base 2.

[0006] The input signal is calculated based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal. ,

[0007] The shift calculation results are summed up to obtain a filtering output result.

[0008] In a possible implementation manner, based on a preset quantization bit number m, the impulse response coefficient of the digital filter is quantized to obtain a quantization result of the impulse response of the digital filter. , specifically including,

[0009] Calculate the maximum quantized amplitude M of the digital filter impulse response function h(k), wherein the maximum quantized amplitude M is the absolute value of the maximum value of the real part and the imaginary part of all impulse responses,

[0010] Based on the preset quantization bit number m and the maximum quantization amplitude M, the minimum quantization interval Δ is calculated,

[0011] Using the minimum quantization interval Δ, at least by dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding off, the real part operation parameters r k and imaginary part operation parameter i k ,

[0012] Based on the real part of the parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and .

[0013] In a possible implementation manner, the calculating the minimum quantization interval Δ based on the preset number of quantization bits and the maximum quantization amplitude M specifically includes calculating the minimum quantization interval Δ using the following formula:

[0014] .

[0015] In a possible implementation manner, the minimum quantization interval Δ is used to obtain the real part operation parameters r respectively by at least dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding the absolute value of the real part and the imaginary part. k and imaginary part operation parameter i k Specifically, the real part operation parameter r is calculated by the following formula k and imaginary part operation parameter i k

[0016] ,

[0017] ,

[0018] in, Indicates rounding down. Indicates rounding up.

[0019] In one possible implementation, , the real part operation parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and , specifically including,

[0020]

[0021]

[0022] in, and are respectively the impulse responses of the digital filter obtained after quantization The real and imaginary parts of .

[0023] In a possible implementation manner, the input signal is calculated based on the quantized digital filter impulse response to obtain a shift calculation result of the input signal. ,, specifically including,

[0024] Based on the digital filter impulse response coefficient and , the multiplication result of the input signal x(k) and the digital filter impulse response q(k) is obtained by performing a shift operation of the shifter on the input signal x(k), and the shift calculation result The calculation formula is:

[0025]

[0026]

[0027]

[0028] in, , N is the order of the digital filter.

[0029] In a possible implementation manner, performing sum calculation on the shift calculation results to obtain a filtering output result specifically includes:

[0030] The shift calculation results are summed and then multiplied by the minimum quantization interval Δ to obtain a filtering output result.

[0031] In a possible implementation manner, the shift calculation results are summed and then multiplied by the minimum quantization interval Δ to calculate the filtering output result, which specifically includes calculating by the following formula:

[0032]

[0033] in, The filter output result.

[0034] In a possible implementation manner, the preset number of quantization bits is a positive integer associated with the number of bits of the digital shifter of the digital filter and the accuracy of the filtered signal.

[0035] A second aspect of the present invention provides a geometric order quantization digital filter, comprising a shifter, an adder, a delay unit, and a data preprocessing unit.

[0036] The data preprocessing unit is used to perform, based on a preset quantization bit number m, quantizing the impulse response coefficient of the digital filter to obtain the quantization result of the impulse response of the digital filter , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient All include the values ​​after exponential operation with base 2.

[0037] The shifter is used to perform calculation on the input signal based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal. ,

[0038] The adder is used to perform addition calculation on the shift calculation results to obtain a filtering output result.

[0039] Beneficial effects of the present invention: The present invention quantizes the impulse response coefficients of the digital filter based on a preset number of quantization bits, and converts the impulse response function into real coefficients. and the imaginary coefficient They all include the values ​​after the exponential operation with base 2, and further obtain the shift calculation result of the digital filter through the shift operation according to the input signal, and finally obtain the filtering output result through the addition calculation. It realizes the conversion of the complex multiplication calculation of the digital filter into the shift calculation of the shifter, greatly reducing the complexity of the digital filter structure and calculation, and improving the signal processing efficiency and processing timeliness. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a flow chart of a geometric order quantization digital filtering method according to an embodiment of the present invention;

[0041] Figure 2a 8-bit shift schematic diagram of the implementation method of the geometric order quantization digital filter in the embodiment of the present invention;

[0042] Figure 2b A 16-bit shift schematic diagram of a method for implementing a geometrically quantized digital filter in an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a geometrically quantized digital filter framework according to an embodiment of the present invention;

[0044] Figure 4 It is a schematic block diagram of the structure of an N=4-order geometric-order quantization digital filter in an embodiment of the present invention;

[0045] Figure 5a-5d It is a schematic diagram of simulation verification of the geometric order quantization digital filtering method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The present invention is further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] It should be noted that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0048] In the above description, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0049] Embodiment 1:

[0050] The filters in current signal processing and chip design are usually a kind of software or hardware composed of digital multipliers, adders and delay units, which have the advantages of high precision and stability, flexible design, etc. With the rapid development of integrated circuits, communication technology and the Internet, more complex application scenarios have put forward higher requirements on the integration of digital filters. However, as the integration of digital filters becomes better, the filters occupy more space, the number of corresponding multipliers, excitation and delay units is increasing, and the complexity of calculation scale is also increasing. This poses higher challenges to the design of miniaturization and stability. At present, there is still no implementation solution for digital filters in the industry that can well balance more and more complex functional modules with miniaturization and stability.

[0051] To solve the above problems, the embodiments of the present invention provide a geometric quantization digital filtering method and a digital filter, as shown in the attached Figure 1 FIG. 1 is a flow chart of a geometric order quantization digital filtering method according to an embodiment of the present invention. The geometric order quantization digital filtering method comprises:

[0052] Step S100: quantizing the impulse response coefficients of the digital filter based on a preset quantization bit number m to obtain a quantization result of the impulse response of the digital filter. , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient All include the value after exponential operation with base 2.

[0053] For a finite impulse response (FIR) filter, the output y(k) of its operation is the convolution of the input signal x(k) and the impulse response h(k), that is, the input signal x(k) at each moment is multiplied by the attenuation or amplification corresponding to the finite impulse response h(k), and then superimposed together as the output signal. The computational complexity of a FIR filter is determined by the order N of its impulse response.

[0054] In a preferred implementation of the embodiment of the present invention, the impulse response h(k) of the finite impulse response filter is a complex number, which includes real and imaginary coefficients. The quantization step in the embodiment of the present invention includes quantizing the impulse response coefficients of the digital filter, specifically including quantizing the real and imaginary coefficients of the impulse response h(k) at the same time to obtain the quantization result of the impulse response of the digital filter. , where the quantification results Including real coefficients and the imaginary coefficient , and transform the original digital filter impulse response coefficients into real coefficients by quantization and the imaginary coefficient All include the value after exponential operation with base 2.

[0055] In the FIR filter impulse response function of the embodiment of the present invention, the real coefficients of the geometrically quantized digital filter and the imaginary coefficients of the geometrically quantized digital filter are converted to integer powers of 2, that is, the real part and the imaginary part of the impulse response h(k) are replaced by the geometric series {0, ±2^0, ±2^1, ±2^2, ..., ±2^m}, thereby generating the geometrically quantized filter coefficients q(k).

[0056] It should be noted that in other implementations of the embodiments of the present invention, when the impulse response h(k) coefficient is a single real number, it can be understood that the imaginary coefficient is 0, or when the impulse response h(k) coefficient is a single imaginary number, it can be understood that the real coefficient is 0.

[0057] The preset number of quantization bits in the embodiment of the present invention is a positive integer associated with the number of bits of the digital shifter of the digital filter and the accuracy of the filtered signal. The number of quantization bits is selected and preset by a technician in this field according to the specific hardware structure of the digital circuit. One implementation method is to select according to the number of bits of the shift register and the signal accuracy matching in an FPGA implementation. For example, when a 16-bit shift register is selected, the ADC digital-to-analog conversion occupies 10 bits. The technicians in this field select 6 bits as the preset number of quantization bits in the geometric quantization digital filtering method in the embodiment of the present invention.

[0058] In a preferred implementation of step S100 in the embodiment of the present invention, based on a preset quantization bit number m, the impulse response coefficient of the digital filter is quantized to obtain the quantization result of the impulse response of the digital filter. , specifically including,

[0059] Step S101: Calculate the maximum quantized amplitude M of the digital filter impulse response function h(k), the maximum quantized amplitude M is the absolute value of the maximum value of the real part and the imaginary part of all impulse responses, that is, the maximum quantized amplitude M is calculated by the following formula:

[0060]

[0061] Step S102: Based on the preset quantization bit number m and the maximum quantization amplitude M, the minimum quantization interval Δ is calculated. The minimum quantization interval Δ can be calculated by the following formula:

[0062] .

[0063] By setting the absolute value of the maximum value in the real part and the imaginary part of all impulse responses as the maximum quantization amplitude, the quantization range required for the original digital filter in the quantization process can be determined, and based on the maximum quantization amplitude and the preset number of quantization bits, the minimum quantization interval can be further accurately determined. In this way, the actual state of the specific impulse response coefficients of different digital filters can be combined to accurately set the accurate quantization interval, ensuring that the accuracy between the convolution calculation completed by combining the shifter substitution on the basis of the quantized impulse response function and the convolution calculation directly completed by the original unquantized impulse response function is within an acceptable range in practical applications.

[0064] Step S103: Using the minimum quantization interval Δ, at least by dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding off, respectively obtain the real part operation parameters r k and imaginary part operation parameter i k , where the real part operation parameter r k and imaginary part operation parameter i k Calculated by the following formula

[0065] ,

[0066] ,

[0067] in, Indicates rounding down. Indicates rounding up. In a preferred implementation, the nearest integer can be rounded up or down according to the rounding principle.

[0068] Step S104: Calculate the parameter r based on the real part k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and .

[0069] The exponential operation with base 2 under the preset conditions in the embodiment of the present invention can be based on r k The relationship between 0 and real part quantization coefficient is determined , based on i k The relationship between 0 and 0 determines the imaginary quantization coefficient .

[0070] Specifically, the digital filter impulse response quantization result and Calculated by the following formula

[0071]

[0072]

[0073] in, and are respectively the impulse responses of the digital filter obtained after quantization The real and imaginary parts of .

[0074] In the embodiment of the present invention, the real coefficient and the imaginary coefficient They all include values ​​after exponential operations with base 2. Based on the calculation principle of binary multiplier, after converting the impulse response coefficients into values ​​after exponential operations with base 2, the complexity of the digital filter structure and calculation can be greatly reduced by converting the complex multiplication calculation of the digital filter into the shift calculation of the shifter.

[0075] The embodiment of the present invention also includes step S200: calculating the input signal based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal .

[0076] After step S100 quantizes the impulse response coefficients of the digital filter to integer powers of 2, the multiplication calculations in the subsequent convolution operations can be substantially converted into shift calculations. Compared with complex multiplication calculations, shift calculations can effectively reduce the complexity and resource consumption of calculations, and can improve the accuracy and stability of calculations under complex calculation amounts.

[0077] In a preferred implementation of the embodiment of the present invention, step S200 specifically includes:

[0078] Based on the digital filter impulse response coefficient and , the multiplication result of the input signal x(k) and the digital filter impulse response q(k) is obtained by performing a shift operation of the shifter on the input signal x(k), and the shift calculation result The calculation formula is:

[0079]

[0080]

[0081]

[0082] in, , N is the order of the digital filter.

[0083] The embodiment of the present invention also includes step S300: performing sum calculation on the shift calculation results to obtain a filtering output result.

[0084] As the convolution operation in digital signal processing generally includes a multiplication operation and an addition operation, in a preferred implementation of the embodiment of the present invention, after the multiplication operation is completed in step S200, step 300 completes the corresponding addition operation.

[0085] In a preferred implementation manner of the embodiments of the present invention, the addition calculation includes not only a calculation method of directly accumulating multiple sum terms, but also assigning a coefficient to each sum term and then performing an addition operation, wherein the coefficients may be the same or different. It may also include assigning a coefficient to each sum term, summing the total number and then assigning a multiplication coefficient, and using the result of the multiplication calculation as the final calculation result of the addition operation.

[0086] In a preferred implementation of the present invention, step S300 specifically includes summing the shift calculation results and then multiplying them by the minimum quantization interval Δ to calculate and obtain a filtering output result. The filtering output result is recorded as , can be calculated by the following formula:

[0087]

[0088] in, The filter output result.

[0089] The embodiment of the present invention quantizes the impulse response coefficients of the digital filter based on a preset number of quantization bits, and converts the impulse response function into real part coefficients. and the imaginary coefficient They all include the values ​​after the exponential operation with base 2, and further obtain the shift calculation result of the digital filter through the shift operation according to the input signal, and finally obtain the filtering output result through the addition calculation. It realizes the conversion of the complex multiplication calculation of the digital filter into the shift calculation of the shifter, greatly reducing the complexity of the digital filter structure and calculation, and improving the signal processing efficiency and processing timeliness.

[0090] In addition, the shifted signal is summed and multiplied with the minimum quantization interval value. Since the quantization interval is inversely proportional to the number of quantization bits, the minimum quantization interval value corresponds to the maximum number of quantization bits. The larger the number of quantization bits, the closer it is to the actual output filter signal, thereby reducing the error of the filter signal at the corresponding output moment, ensuring the precise correspondence between the shift operation and addition operation after quantization and the actual convolution operation, thereby realizing the feasibility of the geometric quantization digital filtering method of the embodiment of the present invention in practice.

[0091] It should be noted that the digital filtering described in the geometrically quantized digital filtering method in the embodiment of the present invention, in addition to specifically referring to the filtering method implemented by convolution operation in the field, can also include correlation calculations including autocorrelation and cross-correlation. The geometrically quantized digital filtering method in the embodiment of the present invention can also be used to reduce the complexity of the hardware and software structure and calculation of the computing module, and improve the signal processing efficiency and processing timeliness.

[0092] As attached Figure 2a FIG. 8 is a schematic diagram of an 8-bit shift of a method for implementing a geometric order quantization digital filter in an embodiment of the present invention. In which, an 8-bit shifter is taken as an example, where b7 is a sign bit, LSB is the least significant bit, and MSB is the most significant bit. When performing a shift operation, if =1 or , then all bits except the sign bit b7 are shifted to the right by 1 bit. or , the sign bit remains unchanged, and the vacant LSB bits are filled with zeros after shifting.

[0093] As attached Figure 2b As shown in FIG. 1 , a schematic diagram of a 16-bit shift of a method for implementing a geometric order quantization digital filter in an embodiment of the present invention is shown; wherein, a 16-bit shifter is taken as an example, wherein b15 is a sign bit. When performing a shift operation, if =8 or , then all bits except the sign bit b15 are shifted 3 bits to the right. or , the sign bit is flipped. The vacant LSB is filled with zero after the shift.

[0094] The schematic diagram of the geometric quantization digital filter framework in the embodiment of the present invention is shown in the attached figure. Figure 3 As shown, the geometric order quantization digital filter 200 includes a shifter 201 , an adder 202 , a delay unit 203 , and a data preprocessing unit 204 .

[0095] The data preprocessing unit 204 is used to perform, based on a preset quantization bit number m, quantizing the impulse response coefficient of the digital filter to obtain the quantization result of the impulse response of the digital filter. , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient All include the values ​​after exponential operation with base 2.

[0096] The shifter 201 is used to perform a calculation on the input signal based on the quantized digital filter impulse response to obtain a shift calculation result of the input signal. .

[0097] In other preferred implementations of the embodiments of the present invention, the specific execution method of quantization operation, shift operation, and addition operation of the geometric quantization digital filter is the same as the above-mentioned geometric quantization digital filtering method, and will not be repeated here.

[0098] As attached Figure 4 As shown, the implementation of N = 4 order geometric order quantization filter can be used Figure 4 The digital filter schematic block diagram is described in the attached Figure 4 , when the input discrete complex signal x(k) is delayed by z^(-1) successively, the real and imaginary parts of the corresponding digital filter coefficients are shifted respectively, and the convolution expansion after shift replacement is calculated:

[0099]

[0100] Get s(k,0), s(k,1), s(k,2) and s(k,3), then add s(k,0), s(k,1), s(k,2) and s(k,3), multiply the sum by △ to get y^' (k), then y^' (k) is the result of x(k) after filtering.

[0101] In order to illustrate the error between the convolution operation and the direct convolution operation implemented by the above-mentioned quantization operation, shift operation, and addition operation in the embodiment of the present invention, and then evaluate the performance of the geometrically quantized digital filtering method and the geometrically quantized digital filter in the embodiment of the present invention, the attached Figure 5a -Attached Figure 5d The result analysis of simulation verification is shown.

[0102] In this embodiment, in order to simulate and verify the proposed geometric order quantization digital filter implementation method, the quantization bit number m=1, 2, 3, and 4 are respectively taken for convolution calculation, and compared with the conventional convolution algorithm. According to the experimental comparison results, it can be seen that the quantization bit number m and the corresponding mean absolute percentage error (MAPE) result are marked in the figure.

[0103] The MAPE measurement method is used to calculate the error between the results of this method and the traditional convolution method:

[0104]

[0105] It can be seen from the accompanying drawings that as the number of quantization bits m increases, the calculation results of the present method are getting closer and closer to the calculation results of the conventional convolution method, which is consistent with the formula.

[0106] Therefore, by using the geometric order quantization digital filter and its implementation method proposed in the present invention, the operation efficiency is greatly improved, the hardware (including storage and calculation) resources are reduced, and the implementation complexity is reduced while the result is close to the traditional filter output.

[0107] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0108] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A geometric quantization digital filtering method, characterized in that: The method comprises, Based on the preset quantization bit number m, the impulse response coefficient of the digital filter is quantized to obtain the quantization result of the impulse response of the digital filter , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient The digital filter impulse response coefficients are quantized based on the preset quantization bit number m to obtain the digital filter impulse response quantization result. , specifically including, Calculate the maximum quantized amplitude M of the digital filter impulse response function h(k), wherein the maximum quantized amplitude M is the absolute value of the maximum value of the real part and the imaginary part of all impulse responses, Based on the preset number of quantization bits m and the maximum quantization amplitude M, a minimum quantization interval Δ is calculated. The minimum quantization interval Δ is calculated based on the preset number of quantization bits m and the maximum quantization amplitude M, specifically including: using the following formula to calculate the minimum quantization interval Δ: , Using the minimum quantization interval Δ, at least by dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding off, the real part operation parameters r k and imaginary part operation parameter i k , Based on the real part of the parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and , the real part operation parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and , specifically including, calculated by the following formula, in, and are respectively the impulse responses of the digital filter obtained after quantization The real and imaginary parts of The input signal is calculated based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal. , the input signal is calculated based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal , specifically including, Based on the quantized impulse response coefficients of the digital filter and , the multiplication result of the input signal x(k) and the digital filter impulse response q(k) is obtained by performing a shift operation of the shifter on the input signal x(k), and the shift calculation result The calculation formula is: in, , N is the order of the digital filter, The shift calculation results are summed to obtain a filtering output result, wherein the summing up of the shift calculation results to obtain the filtering output result specifically includes summing the shift calculation results and then multiplying them by the minimum quantization interval Δ to obtain the filtering output result, wherein the summing up of the shift calculation results and then multiplying them by the minimum quantization interval Δ to obtain the filtering output result specifically includes calculating by the following formula: in, The filter output result.

2. The geometric order quantization digital filtering method according to claim 1, characterized in that: The minimum quantization interval Δ is used to obtain the real part operation parameters r respectively by at least dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding the absolute value of the real part and the imaginary part. k and imaginary part operation parameter i k , specifically including calculating the real part operation parameter r by the following formula k and imaginary part operation parameter i k , in, Indicates rounding down. Indicates rounding up.

3. The geometric order quantization digital filtering method according to claim 1, characterized in that: in, 。 4. The geometric order quantization digital filtering method according to claim 1, characterized in that: The preset number of quantization bits is a positive integer associated with the number of bits of the digital shifter of the digital filter and the accuracy of the filtered signal.

5. A geometrically quantized digital filter, characterized in that: Including shifter, adder, delay unit, and data preprocessing unit, The data preprocessing unit is used to perform, based on a preset quantization bit number m, quantizing the impulse response coefficient of the digital filter to obtain the quantization result of the impulse response of the digital filter , the quantitative results Including real coefficients and the imaginary coefficient , the real coefficient and the imaginary coefficient The digital filter impulse response coefficients are quantized based on the preset quantization bit number m to obtain the digital filter impulse response quantization result. , specifically including, Calculate the maximum quantized amplitude M of the digital filter impulse response function h(k), wherein the maximum quantized amplitude M is the absolute value of the maximum value of the real part and the imaginary part of all impulse responses, Based on the preset number of quantization bits m and the maximum quantization amplitude M, a minimum quantization interval Δ is calculated. The minimum quantization interval Δ is calculated based on the preset number of quantization bits m and the maximum quantization amplitude M, specifically including: using the following formula to calculate the minimum quantization interval Δ: , Using the minimum quantization interval Δ, at least by dividing the absolute value of the real part and the imaginary part of the impulse response h(k) and rounding off, the real part operation parameters r k and imaginary part operation parameter i k , Based on the real part of the parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and , the real part operation parameter r k and imaginary part operation parameter i k , the quantized impulse response of the digital filter is obtained by exponential operation with base 2 under preset conditions. and , specifically including, calculated by the following formula, in, and are respectively the impulse responses of the digital filter obtained after quantization The real and imaginary parts of The shifter is used to perform calculation on the input signal based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal. , the input signal is calculated based on the quantized digital filter impulse response to obtain the shift calculation result of the input signal , specifically including, Based on the quantized impulse response coefficients of the digital filter and , the multiplication result of the input signal x(k) and the digital filter impulse response q(k) is obtained by performing a shift operation of the shifter on the input signal x(k), and the shift calculation result The calculation formula is: in, , N is the order of the digital filter, The adder is used to perform summing calculations on the shift calculation results to obtain a filtering output result, wherein the summing calculations on the shift calculation results to obtain a filtering output result specifically include summing the shift calculation results and then multiplying them by the minimum quantization interval Δ to obtain a filtering output result, and summing the shift calculation results and then multiplying them by the minimum quantization interval Δ to obtain a filtering output result, wherein the summing calculations on the shift calculation results and then multiplying them by the minimum quantization interval Δ to obtain a filtering output result specifically include calculating by the following formula: in, The filter output result.

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