Method and device for merging multiple source data in telemetering system

Abstract

The invention discloses a method and device for merging data of multiple sources in a telemetering system, and relates to the technical field of channel estimation, and the method comprises the following steps: obtaining information bits received by multiple signal sources, and dynamically evaluating the signal-to-noise ratios of received signals of the multiple signal sources; weights are allocated to information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources, and the signal-to-noise ratios of the received signals of the signal sources are in direct proportion to the allocated weights; and quantizing information bits received by the signal sources into 1 and-1, and combining the information bits received by the signal sources based on the distribution weight to obtain combined data. According to the method, the limitation that traditional optimal source selection depends on a single signal source is overcome, and the reliability of the system under complex and dynamic channel conditions is improved by weighting and combining multiple source data. In addition, optical fiber bandwidth resources are saved, and the transmission cost is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of channel estimation, and specifically to a method and device for merging multiple source data in a telemetry system. Background Art

[0002] In modern telemetry systems, accurate data transmission and efficient merging are the keys to achieving stable communication and high-performance telemetry. Traditional best source selection methods usually rely on a single signal source or path for data transmission. This method can work effectively when the signal quality is good and the channel conditions are stable, but its performance drops significantly in an environment where the signal quality fluctuates greatly or the multipath interference is severe. Traditional best source selection methods usually select the optimal source by evaluating the signal strength or signal-to-noise ratio (SNR) of multiple data sources, but this method cannot fully consider the mutual influence or complementary effect between signal sources, resulting in the system being unable to effectively utilize the advantages of all data sources in a dynamic channel or complex multipath environment, thereby reducing the stability of the telemetry system and the accuracy of data transmission.

[0003] In addition, in traditional telemetry systems, the log-likelihood ratio (LLR) is widely used for soft demodulation, representing the probability information of each transmitted bit. Although the LLR can provide richer signal information than hard bits, its use of 8-bit data significantly increases the number of bits transmitted per bit, resulting in the telemetry system consuming more bandwidth resources to transmit data in the case of limited channel bandwidth. This high bandwidth requirement for this data representation method will become a constraint on system efficiency and cost in resource-constrained environments, especially in fiber optic transmission or wireless telemetry systems. Summary of the Invention

[0004] To solve the deficiencies mentioned in the above background art, the purpose of the present invention is to provide a method and device for merging multiple source data in a telemetry system.

[0005] In a first aspect, the purpose of the present invention can be achieved by the following technical solution: A method for merging multiple source data in a telemetry system, the method comprising the following steps:

[0006] Obtain the information bits received by multiple signal sources, and dynamically evaluate the signal-to-noise ratio of the received signals of the multiple signal sources;

[0007] Assign weights to the information bits received by the signal sources based on the signal-to-noise ratio of the received signals of the multiple signal sources, wherein the magnitude of the signal-to-noise ratio of the received signal of the signal source is proportional to the magnitude of the assigned weight;

[0008] Quantize the information bits received by the signal sources into 1 and -1, and merge the information bits received by the signal sources based on the assigned weights to obtain merged data.

[0009] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: The process of dynamically evaluating based on the aircraft telemetry data to obtain the signal-to-noise ratio of the aircraft telemetry data is as follows:

[0010] The sliding window method is used to calculate the SNR value of the received signal of each signal source. The SNR value is dynamically calculated according to the signal sampling within the time window. Through the channel feedback mechanism, the ground station and the aircraft continuously exchange channel state information.

[0011] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: The calculation formula of the SNR value is as follows:

[0012]

[0013] In the formula, P signal represents the signal power, and P noise represents the noise power.

[0014] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: The calculation process of allocating weights to the information bits received by the signal source based on the signal-to-noise ratio of the received signals of multiple signal sources is as follows:

[0015] The weighting coefficient w i of each signal source is calculated by the formula:

[0016]

[0017] where N is the total number of signal sources, and SNR i is the signal-to-noise ratio of the i-th path.

[0018] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: The calculation process of quantifying the information bits received by the signal source into 1 and -1:

[0019] When bit = 1, D = 1, when bit = 0, D = -1, where D is the quantized data and bit represents the received data bit.

[0020] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: The calculation process of combining the information bits received by multiple signal sources based on the allocated weights:

[0021] The quantized data is combined according to the weights. Suppose there are N data sources, and the quantized data are D 1 , D 2 , …, D N , and the weights are w 1 , w 2 , …, w N, then the merged data is obtained through weighted average:

[0022]

[0023] where D final is the merged data, sign represents the sign function, and finally the merged data D final is mapped to 0 and 1 to obtain the finally merged bit data.

[0024] In a second aspect, to achieve the above object, the present invention discloses a merging system for multiple source data in a telemetry system, including:

[0025] A signal-to-noise ratio calculation module, configured to obtain aircraft telemetry data, perform dynamic evaluation based on the aircraft telemetry data, and obtain the signal-to-noise ratio of the aircraft telemetry data;

[0026] A weight allocation module, configured to allocate weights to the information bits received by the signal source based on the signal-to-noise ratios of the received signals of multiple signal sources, where the magnitude of the signal-to-noise ratio of the received signal of the signal source is proportional to the magnitude of the allocated weight;

[0027] A data merging module, which quantifies the information bits received by the signal source into 1 and -1, and merges the information bits received by multiple signal sources based on the allocated weights to obtain merged data.

[0028] Combined with the second aspect, in some implementation manners of the second aspect, the device further includes: The process by which the signal-to-noise ratio calculation module performs dynamic evaluation based on the aircraft telemetry data to obtain the signal-to-noise ratio of the aircraft telemetry data is as follows:

[0029] The sliding window method is used to calculate the signal-to-noise ratio SNR value of the signal received by each signal source, and the SNR value is dynamically calculated according to the signal sampling within the time window. Through the channel feedback mechanism, the ground station and the aircraft continuously exchange channel state information;

[0030] The calculation formula of the SNR value is as follows:

[0031]

[0032] where P signal represents the signal power, and P noise represents the noise power.

[0033] The process by which the weight allocation module allocates weights to the information bits received by the signal source based on the signal-to-noise ratios of the received signals of multiple signal sources is as follows:

[0034] The weighting coefficient w i of each signal source is calculated by the formula:

[0035]

[0036] where N is the total number of signal sources, and SNR i is the signal-to-noise ratio of the i-th path;

[0037] The process of the data merging module quantifying the information bits received by the signal sources into 1 and -1:

[0038] When bit = 1, D = 1. When bit = 0, D = -1. Where D is the quantized data and bit represents the hard bit. The process of the data merging module merging the information bits received by multiple signal sources based on the assigned weights:

[0039] Merge the quantized data according to the weights. Suppose there are N data sources, and the quantized data are D 1 , D 2 , …, D N , and the weights are w 1 , w 2 , …, w N , then the merged data is obtained by weighted average:

[0040]

[0041] In the formula, D final is the merged data. sign represents the sign function. Finally, map the merged data D final to 0 and 1 to obtain the finally merged bit data.

[0042] In another aspect of the present invention, to achieve the above object, a terminal device is disclosed, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores a computer program capable of running on the processor. When the processor loads and executes the computer program, it adopts a method for merging multiple source data in a telemetry system as described above.

[0043] In yet another aspect of the present invention, to achieve the above object, a computer-readable storage medium is disclosed. The computer-readable storage medium stores a computer program. When the computer program is loaded and executed by the processor, it adopts a method for merging multiple source data in a telemetry system as described above.

[0044] Advantages of the present invention:

[0045] The present invention significantly improves the reliability and stability of the telemetry system by weighted merging of data from multiple signal sources. The system can dynamically evaluate the quality of signal sources, adaptively adjust weights, and ensure the accuracy of data merging. While reducing bandwidth requirements, it improves data transmission efficiency, reduces transmission costs, optimizes resource utilization, and is particularly suitable for complex channels and bandwidth-constrained environments, providing an efficient and economical telemetry solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0047] Figure 1 is a schematic flowchart of the method of the present invention;

[0048] Figure 2 is a schematic diagram of the bit error rate performance of merging three data sources when the signal-to-noise ratios of the three data sources are the same in the present invention;

[0049] Figure 3 is a schematic diagram of the bit error rate performance of merging three data sources when the signal-to-noise ratios of the three data sources are different in the present invention;

[0050] Figure 4 is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0052] Embodiment 1:

[0053] The following introduces the relevant terms involved in the embodiments of the present application:

[0054] A telemetry system refers to a system that has the functions of measuring, transmitting, and processing certain parameters of a measured object at a certain distance, that is, a system that transmits the measured values of the object parameters at a short distance to a measurement station at a long distance to achieve long-distance measurement. A telemetry system generally consists of three major parts: an input device, a data transmission device, and a terminal device. Among them, the data transmission device includes devices that multiplex, transmit, receive, and demultiplex multiple signals from the input device. The working principle of a telemetry system involves aspects such as information acquisition, information transmission, and information processing. A telemetry system is essentially a type of multi-channel data transmission system. In order to complete the transmission of multiple-channel information using one channel, multiplexing technology can be adopted.

[0055] As Figure 1 shown, a method for combining multiple source data in a telemetry system, the method includes the following steps:

[0056] S101: Obtain the information bits received by multiple signal sources, and dynamically evaluate the signal-to-noise ratio (SNR) of the received signals of the multiple signal sources;

[0057] The process of dynamically evaluating the signal-to-noise ratio of the received signals of multiple signal sources is as follows:

[0058] Use a sliding window method to calculate the SNR value of the received signal of each signal source, dynamically calculate the SNR value based on the signal samples within the time window, and continuously exchange channel state information between the ground station and the aircraft through a channel feedback mechanism.

[0059] The calculation formula for the SNR value is as follows:

[0060]

[0061] In the formula, P signal represents the signal power, and P noise represents the noise power.

[0062] S102: Allocate weights to the information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources, where the magnitude of the signal-to-noise ratio of the received signal of the signal source is proportional to the magnitude of the allocated weight;

[0063] The process of allocating weights to the information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources is as follows:

[0064] The weighting coefficient w i of each signal source is calculated by the formula:

[0065]

[0066] where N is the total number of signal sources, and SNR i is the signal-to-noise ratio of the i-th path.

[0067] S103: Quantize the information bits received by the signal source into 1 and -1, and combine the information bits received by multiple signal sources based on the assigned weights to obtain combined data.

[0068] Calculation process of quantizing the information bits received by the signal source into 1 and -1:

[0069] When bit = 1, D = 1. When bit = 0, D = -1. Where D is the quantized data and bit represents the hard bit. Calculation process of combining the information bits received by multiple signal sources based on the assigned weights:

[0070] Combine the quantized data according to the weights. Suppose there are N data sources, and the quantized data are D 1 , D 2 , …, D N , and the weights are w 1 , w 2 , …, w N , then the combined data is obtained by weighted average:

[0071]

[0072] In the formula, D final is the combined data. sign represents the sign function. Finally, map the combined data D final to 0 and 1 to obtain the finally combined bit data.

[0073] Specifically, the solution of the present invention will be further elaborated by the following embodiments:

[0074] Simulation conditions

[0075] For the current simulation channel, a multipath channel is selected. The time delays of the nine paths of the first channel are 0 ns, 30 ns, 150 ns, 310 ns, 370 ns, 710 ns, 1090 ns, 1730 ns, and 2510 ns respectively, and the path gains are 0 dB, -1.5 dB, -1.4 dB, -3.6 dB, -0.6 dB, -9.1 dB, -7 dB, -12 dB, and -16.9 dB respectively. The time delays of the nine paths of the second channel are 0 ns, 30 ns, 150 ns, 310 ns, 370 ns, 710 ns, 1090 ns, 1730 ns, and 2510 ns respectively, and the path gains are 0 dB, -1.5 dB, -1.4 dB, -3.6 dB, -0.6 dB, -9.1 dB, -7 dB, -12 dB, and -16.9 dB respectively. The time delays of the nine paths of the third channel are 0 ns, 30 ns, 150 ns, 310 ns, 370 ns, 710 ns, 1090 ns, 1730 ns, and 2510 ns respectively, and the path gains are 0 dB, -1.5 dB, -1.4 dB, -3.6 dB, -0.6 dB, -9.1 dB, -7 dB, -12 dB, and -16.9 dB respectively. The three channels have different frequency domain responses. 3 / 4 code rate coding is used. The communication system contains 1200 subcarriers and the modulation method used is QPSK.

[0076] Under the above simulation conditions, the system uses three ground stations to receive the telemetry data from an aircraft. The receiving end has ideal channel estimation.

[0077] Simulation results:

[0078] Figure 2 When simulating the BER performance of combining the three source data when the signal-to-noise ratios of the three ground stations are the same, it can be seen that compared with the traditional best source selection relying on a single signal source, the method of combining multiple source data adopted by the present invention significantly improves the BER performance, and the gain is about 8.2 dB.

[0079] Figure 3 When simulating the BER performance of combining the three source data when the signal-to-noise ratios of the three ground stations are different, it can be seen that compared with the traditional best source selection relying on a single signal source, the method of combining multiple source data adopted by the present invention can dynamically adjust the weight of each data source during combination, giving a higher weight to the data source with a higher signal-to-noise ratio, and can also have a good gain when the signal-to-noise ratios of multiple data sources are different, and the gain is about 7.7 dB.

[0080] From the above simulation results, it can be seen that the method for merging multiple source data proposed in this paper overcomes the shortcoming of the traditional optimal source selection relying on a single data source and is superior to the traditional scheme in terms of bit error rate performance. Especially when the signal-to-noise ratios of multiple signal sources are different, the merging weights can be adaptively adjusted according to the signal-to-noise ratio, showing strong adaptability. In addition, the present invention does not need to transmit 8-bit LLR data, greatly saving the transmission bandwidth. Therefore, the present invention shows higher reliability and bit error rate performance under complex aviation channel conditions, providing an efficient solution for the telemetry communication system.

[0081] Embodiment 2: Second aspect, as Figure 4 shown, to achieve the above object, the present invention discloses a merging system for multiple source data in a telemetry system, including:

[0082] A signal-to-noise ratio calculation module 11, configured to obtain aircraft telemetry data, perform dynamic evaluation based on the aircraft telemetry data, and obtain the signal-to-noise ratio of the aircraft telemetry data;

[0083] A weight allocation module 12, configured to allocate weights to the information bits received by the signal source based on the signal-to-noise ratios of the received signals of multiple signal sources, wherein the magnitude of the signal-to-noise ratio of the received signal of the signal source is proportional to the magnitude of the allocated weight;

[0084] A data merging module 13, configured to quantize the information bits received by the signal source into 1 and -1, and merge the information bits received by multiple signal sources based on the allocated weights to obtain merged data.

[0085] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions, specifically for loading and executing one or more instructions in the computer storage medium to implement the above method.

[0086] It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is run by a processor, the above-mentioned method is executed. The storage medium may adopt any combination of one or more computer-readable media. The computer-readable media may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electro-magnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.

[0087] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic expressions 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.

[0088] The above shows and describes the basic principles, main features, and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure will have various changes and improvements, and these changes and improvements all fall within the scope of the present disclosure claimed.

Claims

1. A method for merging multiple source data in a telemetry system, characterized in that: The method comprises the following steps: Acquire information bits received by multiple signal sources and dynamically evaluate the signal-to-noise ratios of received signals of the multiple signal sources; Based on the signal-to-noise ratio of the received signals of the multiple signal sources, weights are assigned to the information bits received by the signal sources, wherein the signal-to-noise ratio of the received signals of the signal sources is proportional to the size of the assigned weights; The information bits received by the signal source are quantized into 1 and -1, and the information bits received by the signal source are combined based on the assigned weights to obtain combined data.

2. The method for merging multiple source data in a telemetry system according to claim 1, characterized in that: The process of dynamically evaluating the signal-to-noise ratio of received signals from multiple signal sources is as follows: The sliding window method is used to calculate the signal-to-noise ratio (SNR) value of the signal received by each ground station. The SNR value is dynamically calculated based on the signal sampling within the time window. Through the channel feedback mechanism, the ground station and the aircraft continuously exchange channel status information.

3. The method for merging multiple source data in a telemetry system according to claim 2, characterized in that: The calculation formula of the SNR value is as follows: Where P signal Represents the signal power, P noise Represents the noise power.

4. The method for merging multiple source data in a telemetry system according to claim 1, characterized in that: The calculation process of allocating weights to the information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources is as follows: The weighting factor w of each signal source i The calculation formula is: Where N is the total number of signal sources, SNR i is the signal-to-noise ratio of the signal received by the i-th signal source.

5. The method for merging multiple source data in a telemetry system according to claim 1, characterized in that: The information bits received by the signal source are quantized into 1 and -1: When bit=1, D=1, and when bit=0, D=-1, where D is the quantized data and bit represents the received data bit.

6. The method for merging multiple source data in a telemetry system according to claim 1, characterized in that: The calculation process of combining the information bits received by multiple signal sources based on the distribution weights: The quantized data are merged according to the weights. Suppose there are N ground stations, and the quantized data are D1, D2, ..., D N , the weights are w1,w2,…,w N , then the combined data is obtained by weighted average: Where D final To merge data, sign represents the sign function, and finally the merged data D final Mapping to 0 and 1 can obtain the final combined bit data.

7. A system for merging multiple source data in a telemetry system, characterized in that: include: The signal-to-noise ratio calculation module is used to obtain aircraft telemetry data and dynamically evaluate the signal-to-noise ratio of the received signal of multiple ground stations; A weight allocation module, used for allocating weights to the information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources, wherein the signal-to-noise ratios of the received signals of the signal sources are proportional to the size of the allocated weights; The data merging module is used to quantize the information bits received by the signal source into 1 and -1, and merge the information bits received by the signal source based on the allocated weights to obtain merged data.

8. A system for merging multiple source data in a telemetry system according to claim 7, characterized in that: The process of the signal-to-noise ratio calculation module dynamically evaluating the signal-to-noise ratio of the received signals of multiple ground stations is as follows: The sliding window method is used to calculate the signal-to-noise ratio (SNR) of the signal received by each ground station. The SNR value is dynamically calculated based on the signal sampling within the time window. Through the channel feedback mechanism, the ground station and the aircraft continuously exchange channel status information. The calculation formula of the SNR value is as follows: Where P signal Represents the signal power, P noise represents the noise power; The weight allocation module calculates weights for information bits received by the signal sources based on the signal-to-noise ratios of the received signals of the multiple signal sources as follows: The weighting factor w of each signal source i The calculation formula is: Where N is the total number of signal sources, SNR i is the signal-to-noise ratio of the i-th path; The data merging module quantizes the information bits received by the signal source into 1 and -1 calculation process: When bit=1, D=1, when bit=0, D=-1; where D is the quantized data, bit represents the hard bit; The data merging module performs a calculation process of merging information bits received from multiple signal sources based on the assigned weights: The quantized data are merged according to the weights. Assuming there are N data sources, the quantized data are D1, D2, ..., D N , the weights are w1,w2,…,w N , then the combined data is obtained by weighted average: Where D final To merge data, sign represents the sign function, and finally the merged data D final Mapping to 0 and 1 can obtain the final combined bit data.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, the method for merging multiple source data in a telemetry system according to any one of claims 1 to 6 is adopted.

10. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by the processor, the method for merging multiple source data in a telemetry system according to any one of claims 1 to 6 is adopted.

Images