A surface acoustic wave duplexer design method and application system

Abstract

The application provides a surface acoustic wave duplexer design method and application system, and belongs to the field of electronic communication, and solves the problem of low design efficiency of the surface acoustic wave duplexer. The technical scheme is as follows: the state of an individual in an initial group is initialized, the individual target parameter X of the surface acoustic wave duplexer is given and initialized, the strategy value Y of the individual is calculated, the state of the individual in the group is adjusted according to the self-adjusting function Adap, the random parameter Xj is generated and the random strategy value Yj is calculated. The target parameter Xn of a new individual is generated through the group behavior, the strategy value Yn of the new individual is calculated, the minimum value in Yn is recorded as the current strategy value Yb, the current strategy value Yb of each optimization is stored in the set Yc, the minimum value in the set Yc is the optimal strategy value Ymin, the final target parameter Xfinal corresponding to Ymin is obtained, and the final design result is output. The application has the beneficial effects that the surface acoustic wave duplexer based on the self-adjusting group strategy is efficiently designed, and is easy to be popularized to other surface acoustic wave devices.

Description

Technical Field

[0001] This invention belongs to the field of electronic communications, specifically relating to a surface acoustic wave duplexer design method and application system. Background Technology

[0002] With the increasing aging of the population, falls among the elderly are becoming more frequent. Due to the complex environment surrounding the human body, traditional fall detection systems are easily affected by environmental interference and misjudgments caused by daily activities. Furthermore, traditional systems suffer from poor signal transmission isolation and frequency band separation, leading to severe signal interference and impacting system stability and reliability. Surface Acoustic Wave (SAW) duplexers, as a key component in modern wireless communication systems, are widely used in mobile communication terminals, RF front-end modules, and wireless sensing systems. Their core function is to achieve signal transmission isolation and frequency band separation. SAW duplexers offer high stability and facilitate real-time signal transmission, meeting the needs of fall detection systems in complex environments.

[0003] The widespread use and diversification of electronic devices today have led to complex signal propagation environments, placing higher demands on duplexers, including high isolation, low insertion loss, and miniaturization. Traditional surface acoustic wave (SAW) duplexer designs improve isolation by increasing filter order or adjusting resonant arm parameters. These methods largely rely on empirical trial-and-error and fixed topology optimization, requiring repeated parameter adjustments, resulting in long design cycles and unsatisfactory performance. This is especially true when optimizing multiple parameters such as the number of finger pairs and aperture, making it difficult to guarantee a globally optimal solution.

[0004] Therefore, this invention provides a surface acoustic wave duplexer design method for fall detection systems, achieving efficient fall detection. Summary of the Invention

[0005] This invention provides a surface acoustic wave (SAW) duplexer design method and application system. The method adjusts the state of individuals in a group according to the self-adjustment function Adap, and generates new individuals through group behavior to change the target parameter X. The method optimizes the strategy value Y and finally obtains the design result of the SAW duplexer. It has the advantages of accuracy, convenience and reliability and has strong application value.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] A surface acoustic wave duplexer design method and application system includes the following steps:

[0008] S10. Initialize the state of individuals in the population, set the number of individuals in the population N, the maximum number of optimization attempts MAXGEN, and the current number of optimization attempts. Individual perceived distance Crowding factor and individual step length ,in and These represent the maximum and minimum individual perceived distances, respectively. and These are the maximum and minimum crowding factors, respectively. and These represent the maximum and minimum individual step lengths, and the number of fields of view, respectively. Then, the individual target parameters X of the surface acoustic wave duplexer are given and initialized. The individual target parameters X include the number of indexed bar pairs. And aperture W, define the target category ,in The category representing the current target parameter X is the number of indexed logs FN. Let the category of the current target parameter X be aperture W, and let... ,

[0009] (1);

[0010] in And n represents the ID of the current individual in the group. and These represent the lower and upper limits of the value of the logarithm FN, respectively. and These represent the lower and upper limits for the aperture W value, respectively. This indicates the generation of a random number in the interval [0, 1). Indicates to Rounding down,

[0011] S20. Calculate the individual's strategy value Y, and adjust the state of individuals in the population according to the self-adjustment function Adap.

[0012] S30. Generate random parameters Xj and calculate random policy values ​​Yj. Generate target parameters Xn for new individuals based on group behavior and calculate policy values ​​Yn for the new individuals.

[0013] S40. The current policy value Yb records the minimum value in Yn. The current policy value Yb obtained from each optimization is stored in the set Yc.

[0014] S50, the minimum value in set Yc is the optimal strategy value Ymin, obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result.

[0015] Furthermore, step S20 includes the following steps:

[0016] S21. Calculate the individual's strategy value Y.

[0017] (2);

[0018] in This represents the insertion loss within the passband of the trapezoidal filter. This represents the insertion loss of the trapezoidal filter due to out-of-band rejection. Indicates to Take the absolute value.

[0019] S22. The state of individuals in the group is adjusted according to the self-adjusting function Adap. The individual state adjusted by Adap includes the individual's perceived distance v(gen), crowding factor d(gen), and individual step size s(gen), i.e. Define the initial individual perceived distance Initial crowding factor Initial individual step size ,

[0020] (3);

[0021] The current individual status number Current number of optimization attempts ,and This is the attenuation factor, used to control the magnitude of the attenuation of the self-adjusting function Adap.

[0022] Furthermore, step S30 includes the following steps:

[0023] S31. Generate random parameters Xj and calculate random policy values ​​Yj, in the target parameter Random parameters are generated within the perception distance v(gen). ,

[0024] (4);

[0025] random parameters Substitute into formula (2) to calculate the random policy value ,

[0026] S32. Target parameters for generating new individuals through group behavior ,

[0027] (5);

[0028] Individual step length Crowding factor Number of fields of view Approaching stride , Indicates the direction of random parameters Similar stride length Representing the distance between individuals, the target parameter of the new individual. Substituting into formula (2), we obtain the strategy value of the new individual. .

[0029] Furthermore, step S40 includes the following steps:

[0030] S41. The current policy value Yb records the minimum value in Yn. The current policy value Yb represents the minimum policy value corresponding to the current optimization count gen.

[0031] (6);

[0032] in This indicates obtaining the strategy values ​​of all new individuals. The minimum value in, The number of individuals in the group. This represents the current number of optimization attempts.

[0033] S42. Store the current strategy value Yb obtained from each optimization in the set Yc.

[0034] (7);

[0035] in This represents the maximum number of optimization attempts.

[0036] Furthermore, the surface acoustic wave duplexer design method and application system described above are characterized in that step S50 includes the following steps:

[0037] S51. The minimum value in the set Yc is the optimal policy value Ymin.

[0038] (8);

[0039] (9);

[0040] in This indicates retrieving the individual ID corresponding to the minimum value in set Yc. The optimal individual number is assigned. This means finding the minimum value in the set Yc.

[0041] S52. Obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result.

[0042] (10);

[0043] After obtaining the final target parameter Xfinal, it is output as the final design result.

[0044] This application provides a duplexer, including a surface acoustic wave duplexer based on a self-adjusting population strategy designed by the above design method, for use in a fall detection system.

[0045] This application also provides a fall detection system, characterized in that it includes a surface acoustic wave duplexer as described above.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] This method comprehensively considers global and local optima based on a self-adjusting population strategy. By adjusting the individual states through the self-adjusting function Adap, it reduces the trial-and-error cost and design complexity when designing surface acoustic wave (SAW) duplexers, thereby improving the performance of SAW duplexers. This invention can provide a reliable reference method and offer more options for actual device design. Attached Figure Description

[0048] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0049] Figure 1 This is the overall flow of a surface acoustic wave duplexer design method according to the present invention.

[0050] Figure 2 This is a processing framework diagram of a surface acoustic wave duplexer design method according to the present invention.

[0051] Figure 3 This is a flowchart illustrating the design method of a surface acoustic wave duplexer according to the present invention.

[0052] Figure 4 This is a structural diagram of a duplexer according to a surface acoustic wave duplexer design method of the present invention.

[0053] Figure 5 This is a structural diagram of a resonator for a surface acoustic wave duplexer based on a self-adjusting group strategy according to the present invention.

[0054] Figure 6 The transmission curves and isolation curves of the transmitting trapezoidal filter and the receiving trapezoidal filter are shown in one embodiment of the present invention.

[0055] Figure 7 This is a structural diagram of a fall monitoring system based on a self-adjusting group strategy surface acoustic wave duplexer according to the present invention.

[0056] In the figure, 1 is the transmitting port; 2 is the antenna port; 3 is the receiving port; 4 is the period of the reflector grating; 5 is the aperture; 6 is the period of the interdigital transducer; 7 is the number of finger pairs; 8 is the film thickness; 9 is the number of reflector grating pairs; 10 is the transmission curve of the transmitting trapezoidal filter; 11 is the transmission curve of the receiving trapezoidal filter; and 12 is the isolation curve. Detailed Implementation

[0057] To more clearly illustrate the specific technical solutions of the embodiments of the present invention, the present invention will be further described below in conjunction with implementation examples and accompanying drawings. Obviously, the described implementation examples are only some embodiments of the present invention, not all embodiments. To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. Of course, the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The implementation method and application system of a surface acoustic wave duplexer according to the present invention are as follows:

[0058] See Figures 1 to 3 As shown, the present invention provides a technical solution: a surface acoustic wave duplexer design method and application system, comprising the following steps:

[0059] S10. Initialize the state of individuals in the group, set the number of individuals in the group to N=50, the maximum number of optimization attempts MAXGEN=2000, and the current number of optimization attempts. Individual perceived distance Crowding factor and individual step length ,in and These represent the maximum and minimum individual perceived distances, respectively. and These are the maximum and minimum crowding factors, respectively. and These represent the maximum and minimum individual step lengths, and the number of fields of view, respectively. The surface acoustic wave duplexer uses a piezoelectric substrate material of 36°. The material's parameters include a propagation velocity VB = 4112. The surface acoustic wave duplexer consists of a transmitting trapezoidal filter (TX filter) and a receiving trapezoidal filter (RX filter), and its specific structural composition is as follows: Figure 4As shown, the center frequency of the transmitting trapezoidal filter (TX filter) is determined to be ft0 = 836MHz, and the center frequency of the receiving trapezoidal filter (RX filter) is determined to be fr0 = 879MHz. The series resonators constituting the transmitting trapezoidal filter (TX filter) are defined as T-S1 and T-S2, the parallel resonator constituting the transmitting trapezoidal filter (TX filter) is defined as T-P1, the series resonators constituting the receiving trapezoidal filter (RX filter) are defined as R-S1 and R-S2, and the parallel resonator constituting the receiving trapezoidal filter (RX filter) is defined as R-P1. The resonator structures of the transmitting trapezoidal filter (TX filter) and the receiving trapezoidal filter (RX filter) forming the duplexer are as follows: Figure 5 As shown in Table 1, some parameters of the series and parallel resonators are presented. Then, the individual target parameters X of the surface acoustic wave duplexer are given and initialized. The individual target parameters X include the number of finger pairs. And aperture W, define the target category ,in The category representing the current target parameter X is the number of indexed logs. , Let the category of the current target parameter X be aperture W, and let... ,

[0060] Table 1

[0061]

[0062] (1);

[0063] in And n represents the ID of the current individual in the group. and These represent the lower and upper limits of the value of the logarithm FN, respectively. and These represent the lower and upper limits for the aperture W value, respectively. This indicates the generation of a random number in the interval [0, 1). Indicates to Rounding down,

[0064] S20. Calculate the individual's strategy value Y, and adjust the state of individuals in the population according to the self-adjustment function Adap.

[0065] S30. Generate random parameters Xj and calculate random policy values ​​Yj. Generate target parameters Xn for new individuals based on group behavior and calculate policy values ​​Yn for the new individuals.

[0066] S40. The current policy value Yb records the minimum value in Yn. The current policy value Yb obtained from each optimization is stored in the set Yc.

[0067] S50, the minimum value in set Yc is the optimal strategy value Ymin, obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result.

[0068] As a surface acoustic wave duplexer design method and application system provided by the present invention, step S20 includes the following steps:

[0069] S21. Calculate the individual's strategy value Y.

[0070] (2);

[0071] in This represents the insertion loss within the passband of the trapezoidal filter. This represents the insertion loss of the trapezoidal filter due to out-of-band rejection. Indicates to Take the absolute value.

[0072] S22. The state of individuals in the group is adjusted according to the self-adjusting function Adap. The individual state adjusted by Adap includes the individual's perceived distance v(gen), crowding factor d(gen), and individual step size s(gen), i.e. Define the initial individual perceived distance Initial crowding factor Initial individual step size ,

[0073] (3);

[0074] The current individual status number Current number of optimization attempts ,and The attenuation factor is used to control the magnitude of the attenuation of the self-adjustment function Adap. The self-adjustment results of individual perceived distance v(gen), crowding factor d(gen), and individual step size s(gen) are shown in Table 2.

[0075] Table 2

[0076]

[0077] As a surface acoustic wave duplexer design method and application system provided by the present invention, step S30 includes the following steps:

[0078] S31. Generate random parameters Xj and calculate random policy values ​​Yj, in the target parameter Random parameters are generated within the perception distance v(gen). ,

[0079] (4);

[0080] random parameters Substitute into formula (2) to calculate the random policy value ,

[0081] S32. Target parameters for generating new individuals through group behavior ,

[0082] (5);

[0083] Individual step length Crowding factor Number of fields of view Approaching stride , Indicates the direction of random parameters Similar stride length Representing the distance between individuals, the target parameter of the new individual. Substituting into formula (2), we obtain the strategy value of the new individual. .

[0084] As a surface acoustic wave duplexer design method and application system provided by the present invention, step S40 includes the following steps:

[0085] S41. The current policy value Yb records the minimum value in Yn. The current policy value Yb represents the minimum policy value corresponding to the current optimization count gen.

[0086] (6);

[0087] in This indicates obtaining the strategy values ​​of all new individuals. The minimum value in, The number of individuals in the group. This represents the current number of optimization attempts.

[0088] S42. Store the current strategy value Yb obtained from each optimization in the set Yc.

[0089] (7);

[0090] in This represents the maximum number of optimization attempts.

[0091] As a surface acoustic wave duplexer design method and application system provided by the present invention, step S50 includes the following steps:

[0092] S51. The minimum value in the set Yc is the optimal policy value Ymin.

[0093] (8);

[0094] (9);

[0095] in This indicates retrieving the individual ID corresponding to the minimum value in set Yc. The optimal individual number is assigned. This means finding the minimum value in the set Yc.

[0096] S52. Obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result.

[0097] (10);

[0098] After obtaining the final target parameter Xfinal, the specific design results of Xfinal are shown in Table 3, which are output as the final design results.

[0099] Table 3

[0100] category T-S1 T-S2 T-P1 R-S1 R-S2 R-P1 Xfinal(1, index) (points to the number of logarithms FN) 152 85 187 156 84 181 Xfinal(2,index)(um)(aperture W) 65.7 59.7 186.5 73.2 68.1 198.3

[0101] like Figure 4As shown, the surface acoustic wave duplexer has a transmitting port 1, a transmitting trapezoidal filter (TX filter), an antenna port 2, a receiving trapezoidal filter (RX filter), and a receiving port 3. The transmitting port 1 and antenna port 2 are connected to the transmitting trapezoidal filter (TX filter), and the antenna port 2 and receiving port 3 are connected to the receiving trapezoidal filter (RX filter). The trapezoidal filter of this invention, consisting of one series resonator and one parallel resonator, is a first-order trapezoidal filter. The trapezoidal filter of this invention is a 2.5-order filter. The transmitting trapezoidal filter consists of three series resonators and two parallel resonators, where the series resonators are T-S1 and T-S2, and the parallel resonator is T-P1. The receiving trapezoidal filter consists of three series resonators and two parallel resonators, where the series resonators are R-S1 and R-S2, and the parallel resonator is R-P1. The topology of the resonators in the transmitting and receiving trapezoidal filters is T-shaped. The transmitting trapezoidal filter's three resonators—the series resonators T-S1 and T-S2, and the parallel resonator T-P1—are connected to form a T-shape. The three resonators of the receiving trapezoidal filter, namely the series resonators R-S1 and R-S2 and the parallel resonator R-P1, are connected to form a T-shape. The series resonator T-S1 is connected to one end of the transmitting port 1, and its other end is connected to the parallel resonator T-P1 and the series resonator T-S2 respectively. One end of the parallel resonator T-P1 is connected to the series resonators T-S1 and T-S2 respectively, and its other end is grounded. The antenna port 2 is connected to the series resonator T-S1 and the series resonator R-S1 respectively. The series resonator R-S1 is connected to one end of the receiving port 3, and its other end is connected to the parallel resonator R-P1 and the series resonator R-S2 respectively. One end of the parallel resonator R-P1 is connected to the series resonators R-S1 and R-S2 respectively, and its other end is grounded. The surface acoustic wave trapezoidal filter thus constructed has the characteristics of high out-of-band suppression, low insertion loss and miniaturization, which improves the isolation of the passband of the surface acoustic wave duplexer; furthermore, the series resonators T-S1, T-S2, R-S1 and R-S2 and the parallel resonators T-P1 and R-P1 are all surface acoustic wave resonators, which are designed using the method in claim 1, and their specific design parameters are shown in Tables 1 and 3.

[0102] like Figure 5As shown, the single surface acoustic wave (SAW) resonator structure comprises a piezoelectric substrate, two reflective gratings, and an interdigital transducer. Specific parameters of the SAW duplexer resonator include a reflective grating period of 4, an aperture of 5, an interdigital transducer period of 6, a number of finger pairs of 7, a film thickness of 8, and a number of reflective grating pairs of 9. The reflective grating period of 4 is the sum of the widths of the gaps between the midpoints of the two fingers in the reflective grating. The aperture of 5 is the overlap length between two adjacent fingers in the interdigital transducer. The interdigital transducer period of 6 is the sum of the widths of the gaps between the midpoints of the two fingers on the same side of the interdigital transducer. The number of finger pairs between two adjacent fingers in the interdigital transducer is 7. The film thickness of 8 is the thickness of the fingers. The number of reflective grating pairs between two adjacent fingers in the reflective grating is 9. In this invention, the width of the fingers is equal to the width of the gaps between the fingers.

[0103] like Figure 6 As shown, the transmission curves and isolation curves of the transmitting and receiving trapezoidal filters according to an embodiment of the present invention are illustrated. The topology of the resonators in the transmitting and receiving trapezoidal filters is as follows: Figure 4 As shown in Tables 1 and 3, the specific design parameters of the resonator are derived from the transmission curve 10 of the transmitting trapezoidal filter and the transmission curve 11 of the receiving trapezoidal filter. The transmitting and receiving trapezoidal filters of the embodiment have low passband insertion loss and high out-of-band rejection. As shown in the isolation curve 12, the duplexer composed of the transmitting and receiving trapezoidal filters has high isolation in the passband range and the isolation curve is smooth.

[0104] like Figure 7The diagram shows the structural composition of a fall monitoring system based on a self-adjusting group strategy surface acoustic wave duplexer according to the present invention. The fall monitoring system comprises a transmitting link, a wireless communication module, a receiving link, and a power supply module. The transmitting link is characterized by including a sensor group, a signal amplifier, an ADC analog-to-digital converter, a microcontroller, a modulator, a power amplifier PA, and a transmitting trapezoidal filter in the surface acoustic wave duplexer. The sensor group includes a pressure sensor, an acceleration sensor, a heart rate sensor, and a gyroscope sensor for real-time acquisition of human body status data. The signal amplifier amplifies the signal, and the ADC (Analog-to-Digital Converter) converts the human body status data from analog to digital signals. The microcontroller receives the human body status data, transmits it in real-time, and determines whether the person has fallen. If it is determined to be normal activity, no special action is taken, and the system transmits the human body's position data in real-time. If a fall is detected, an alarm signal is transmitted. The modulator modulates the signal output by the microcontroller, converting it into a high-frequency signal suitable for the trapezoidal filter in the surface acoustic wave duplexer. The power amplifier (PA) amplifies the modulated signal to ensure effective signal radiation. The trapezoidal filter removes stray and unwanted frequency components from the signal, eliminating interference to ensure the purity of the transmitted signal meets requirements.

[0105] The wireless communication module includes an antenna, a cloud platform, and a terminal device. The antenna is used to send and receive signals. The cloud platform receives and stores data, analyzes the human health status based on the stored data, and uploads the data to the terminal device in real time. The guardian sends instructions to the cloud platform through the terminal device, and the cloud platform then transmits the instructions to the antenna to remotely control the working status of the monitoring device, enabling or disabling the monitoring function and adjusting the monitoring parameters.

[0106] The receiving link is characterized by comprising a receiving trapezoidal filter, a low-noise amplifier (LNA), a demodulator, a microcontroller, an alarm module, and a display module within a surface acoustic wave (SAW) duplexer. The receiving trapezoidal filter filters the received signal to remove interference and noise. The LNA amplifies the received signal while minimizing noise introduction to ensure signal quality. The demodulator demodulates the amplified signal to recover the original data information. The microcontroller processes the received data and adjusts the system's operating status or executes commands based on feedback information. In the event of a fall, the alarm module triggers a local audible and visual alarm to alert nearby personnel and contact emergency contacts. The display module displays the system status, monitoring data, and alarm information in real time, allowing users to intuitively understand the system's operation. The power supply module provides power to the sensor group, microcontroller, and alarm module.

[0107] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A design method for a surface acoustic wave duplexer, comprising the following steps: S10. Initialize the state of individuals in the population, set the number of individuals in the population N, the maximum number of optimization attempts MAXGEN, and the current number of optimization attempts. Individual perceived distance Crowding factor and individual step length ,in and These represent the maximum and minimum individual perceived distances, respectively. and These are the maximum and minimum crowding factors, respectively. and These represent the maximum and minimum individual step lengths, and the number of fields of view, respectively. Then, the individual target parameters X of the surface acoustic wave duplexer are given and initialized. The individual target parameters X include the number of finger logs FN and the aperture W, and the target category is defined. ,in The category representing the current target parameter X is the number of indexed logs FN. Let the category of the current target parameter X be aperture W, and let... , (1)； in And n represents the ID of the current individual in the group. and These represent the lower and upper limits of the value of the logarithm FN, respectively. and These represent the lower and upper limits for the aperture W value, respectively. This indicates the generation of a random number in the interval [0, 1). Indicates to Rounding down, S20. Calculate the individual's strategy value Y, and adjust the state of individuals in the population according to the self-adjustment function Adap; the method of step S20 includes: S21. Calculate the individual's strategy value Y. (2)； in This represents the insertion loss within the passband of the trapezoidal filter. This represents the insertion loss of the trapezoidal filter due to out-of-band rejection. Indicates to Take the absolute value. S22. The state of individuals in the group is adjusted according to the self-adjusting function Adap. The individual state adjusted by Adap includes the individual's perceived distance v(gen), crowding factor d(gen), and individual step size s(gen), i.e. Define the initial individual perceived distance Initial crowding factor Initial individual step size , (3)； The current individual status number Current number of optimization attempts ,and This is the attenuation factor, used to control the magnitude of the attenuation of the self-adjusting function Adap; Adap min It is the minimum value in the self-adjusting function; S30. Generate random parameters Xj and calculate random policy values ​​Yj. Generate target parameters Xn for new individuals based on group behavior and calculate policy values ​​Yn for the new individuals. S40. The current policy value Yb records the minimum value in Yn. The current policy value Yb obtained from each optimization is stored in the set Yc. S50, the minimum value in set Yc is the optimal strategy value Ymin, obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result.

2. The surface acoustic wave duplexer design method according to claim 1, characterized in that, Step S30 includes the following steps: S31. Generate random parameters Xj and calculate random policy values ​​Yj, in the target parameter Random parameters are generated within the perception distance v(gen). , (4)； random parameters Substitute into formula (2) to calculate the random policy value , S32. Target parameters for generating new individuals through group behavior , (5)； Individual step length Crowding factor Number of fields of view Approaching stride , Indicates the direction of random parameters Similar stride length Representing the distance between individuals, the target parameter of the new individual. Substituting into formula (2), we obtain the strategy value of the new individual. .

3. The surface acoustic wave duplexer design method according to claim 1, characterized in that, Step S40 includes the following steps: S41. The current policy value Yb records the minimum value in Yn. The current policy value Yb represents the minimum policy value corresponding to the current optimization count gen. (6)； in This indicates obtaining the strategy values ​​of all new individuals. The minimum value in, The number of individuals in the group. This represents the current number of optimization attempts. S42. Store the current strategy value Yb obtained from each optimization in the set Yc. (7)； in This represents the maximum number of optimization attempts.

4. The surface acoustic wave duplexer design method according to claim 1, characterized in that, Step S50 includes the following steps: S51. The minimum value in the set Yc is the optimal policy value Ymin. (8)； (9)； in This indicates retrieving the individual ID corresponding to the minimum value in set Yc. The optimal individual number is assigned. This means finding the minimum value in the set Yc. S52. Obtain the final target parameter Xfinal corresponding to Ymin, and output the final design result. (10)； After obtaining the final target parameter Xfinal, it is output as the final design result.

5. A duplexer, characterized in that, This includes a surface acoustic wave duplexer based on a self-adjusting population strategy designed using the design method of claim 1.

6. A fall detection system, characterized in that, Includes the surface acoustic wave duplexer as described in claim 5.

Images