Attitude sensor and hydrophone data alignment method based on OTSM

Abstract

The invention discloses an OTSM-based attitude sensor and hydrophone data alignment method, and belongs to the technical field of ocean monitoring. The method for aligning attitude sensor and hydrophone data based on an OTSM synchronization technology comprises the following steps: inserting a pilot symbol in a signal of a hydrophone through a synchronization algorithm of a time axis and a time delay axis; time delay on different propagation paths is determined by searching a peak value of a pilot signal to perform time synchronization on data, and accurate frequency alignment of data of multiple sensors in a complex environment is realized through Walsh-Hadamard transform frequency compensation by combining a signal containing a pilot symbol. The frequency alignment of the attitude data and the hydrophone data is ensured, and higher synchronization precision is realized.

Description

Technical Field

[0001] The present application belongs to the field of ocean monitoring technology, and in particular, relates to an OTSM-based attitude sensor and hydrophone data alignment method. Background Art

[0002] In the current field of ocean observation and underwater sensing, the synchronous alignment technology of digital hydrophones and attitude sensors is mainly divided into the following methods: 1. Independent acquisition and post-alignment method In this method, the hydrophone and attitude sensor collect data independently, each with its own timestamp, and the data is aligned by an algorithm later. This method relies on independent clock sources, which may cause time drift during the acquisition process. A common practice is to re-match the two sets of data based on the timestamp in the post-processing stage, and align the two sets of data with different frequencies through interpolation or other alignment algorithms. Since the hydrophone and attitude sensor collect data separately, the slight drift of the independent clock source may cause deviation in data time, especially in the long-term acquisition process, the time error caused by the drift is difficult to eliminate. In addition, the data sampling frequencies of different sensors are usually different, the alignment algorithm is complex and the computational cost is high, and the effect is not ideal in applications with high real-time requirements.

[0003] 2. Central clock synchronization method This method uses a unified clock source (such as GPS signals or high-precision internal clocks) to synchronize the timestamps of the hydrophone and attitude sensor. Specifically, the unified time signal emitted by the central clock is transmitted to each sensor via wired or wireless means, and each sensor marks the timestamp based on this clock when collecting data. This method is more limited in application in marine or underwater environments. GPS signals are blocked when transmitted underwater, and even in shallow water areas, fluctuations in GPS signals will affect clock stability. In addition, the use of central clock synchronization methods usually requires high-precision clock equipment, which increases equipment costs, complicates system integration, and makes equipment maintenance difficult, making it unsuitable for long-term deployment.

[0004] 3. Hardware trigger synchronization method This method synchronizes the acquisition process of the hydrophone and attitude sensor in the form of a hardware trigger signal. For example, a trigger signal is sent to the two sensors at the same time to control them to start collecting data at the same time. Hardware triggering can transmit signals through physical connections to ensure that the timestamps of the two sensors are consistent. The design of hardware trigger synchronization requires additional interface devices, which increases the hardware complexity of the system. At the same time, there is a slight delay in the physical transmission of the trigger signal, especially in long-distance or underwater environments, the signal transmission path may be limited, resulting in a decrease in data alignment accuracy. In addition, this method is difficult to cope with dynamic and high-real-time application scenarios.

[0005] The above three existing technical solutions have their own defects in the data synchronization between digital hydrophone and attitude sensor: the independent acquisition and post-alignment method has insufficient time accuracy; the central clock synchronization method is easily restricted in underwater environment and has high equipment cost; the hardware trigger synchronization solution requires a more complex hardware interface design, and the signal transmission delay increases the data error. These technical methods are difficult to achieve accurate alignment of hydrophone and attitude sensor in a dynamic underwater environment with high efficiency and low cost, and cannot solve the technical problem of asynchronous data timestamps between hydrophone and attitude sensor in a dynamic underwater environment. Summary of the invention

[0006] In order to solve the technical problem of the asynchrony of the timestamps of attitude sensor and hydrophone data in the prior art in ocean monitoring, the present application proposes an OTSM-based attitude sensor and hydrophone data alignment method.

[0007] In a first aspect of the present application, the present application discloses a method for aligning data of an attitude sensor and a hydrophone based on OTSM, characterized by comprising: Step S1, independently collecting attitude sensor data and hydrophone data to obtain attitude sensor data sequence A and hydrophone data sequence B; Step S2, creating a time series C, where the time interval of time series C is smaller than the time interval of sequence A and sequence B, so that the timestamps of sequence A and sequence B can find the closest matching point in C; Step S3, inserting a pilot symbol into the signal of the hydrophone, and placing the pilot symbol at a specific position of each frame; Step S4, using a sliding window search method to identify the peak position of the pilot symbol in the Delay-Time domain, thereby determining the delay of the signal on different paths and performing time synchronization on the data; Step S5, after completing the time synchronization, it is necessary to compensate for the frequency offset in the signal to achieve the consistency of the frequency between the attitude sensor and the hydrophone data; Step S6, find the closest T in the attitude sensor data sequence A and the hydrophone data sequence B. C The corresponding data points in sequence A and sequence B are inserted into the corresponding positions in time series C to update time series C; Step S7, checking each time point of the time series C, finding the synchronization point containing both the attitude sensor and the hydrophone data, extracting the data entries that meet the conditions, and generating a new aligned data sequence D; Step S8, outputting the aligned data sequence for subsequent analysis and processing.

[0008] Furthermore, the attitude sensor data in step S1 includes attitude angle, time and acceleration, and the hydrophone data includes sound wave signal, frequency, sound intensity, waveform and time.

[0009] Furthermore, in step S2, the time interval of time series C is shorter than the time intervals of sequence A and sequence B, which includes: the sampling frequency of the attitude sensor is 10 Hz, the sampling frequency of the hydrophone is 5 Hz, and the time interval of time series C is 1 Hz.

[0010] Furthermore, step S2 includes: defining a time series C(T n , tag1, attitude, tag2,hydrophone), select a time point T from the time series C C As the reference time for the current processing; where T n is time, attitude is attitude sensor data, hydrophone is hydrophone data, tag1 and tag2 represent attitude sensor data and hydrophone data tags respectively, and the initial values ​​of tag1 and tag2 are 0.

[0011] Furthermore, step S4 further includes: performing weighted average processing on the delays on different paths to calculate the final synchronization delay, and the calculation formula is: ,in, is the delay of the ith path , N is the number of different signal propagation paths, is the weight of different paths; the received hydrophone signal is delayed compensated according to the weighted average delay, so that the attitude sensor and hydrophone data are synchronized in time.

[0012] Further, step S5 includes: after time synchronization, converting the signal containing the pilot symbol into the delay-sequence domain through Walsh-Hadamard transform, and performing frequency synchronization in the delay-sequence domain using the phase characteristic of the pilot signal.

[0013] Further, performing frequency synchronization using the phase characteristic of the pilot signal in step S5 includes: The carrier frequency offset CFO is calculated using the pilot symbol as the frequency reference, and the estimated CFO value is used to compensate for the frequency drift in the signal to ensure that the frequency of the attitude data and the hydrophone data are aligned.

[0014] Furthermore, step S6 specifically includes: Step S61, search the closest T in sequence A C If a data point T1 matching the timestamp is found, the data is inserted into the corresponding position in the time series C, and tag1=1 is set to mark the data point at T CThere is attitude sensor data at the time point; if no qualifying data point is found, tag1=0; Step S62, searching the closest T in sequence B C If a data point T2 matching the timestamp is found, the data is inserted into the corresponding position in the time series C, and tag2=1 is set to mark the data point at T C There is hydrophone data at the time point; if no qualifying data point is found, tag2=0.

[0015] In a second aspect of the present application, the present application provides a computer device comprising a memory, a processor, and program instructions stored in the memory and executable by the processor, wherein the processor executes the program instructions to implement the steps in any one of the methods described in the first aspect.

[0016] In a third aspect of the present application, the present application provides a computer-readable storage medium storing a computer program, characterized in that when the computer program is executed by a processor, the method described in any one of the first aspects is implemented.

[0017] The present application discloses a method for aligning attitude sensor and hydrophone data based on OTSM, which belongs to the field of ocean monitoring technology. The present application is a method for aligning attitude sensor and hydrophone data based on OTSM synchronization technology. Through the synchronization algorithm of the time axis and the delay axis, a pilot symbol is inserted into the signal of the hydrophone, and the delay on different propagation paths is determined by finding the peak value of the pilot signal to synchronize the data. The signal containing the pilot symbol is combined with the Walsh-Hadamard transform frequency compensation to achieve accurate frequency alignment of data of multiple sensors in complex environments, ensure the frequency alignment of attitude data and hydrophone data, and achieve higher synchronization accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a method for aligning attitude sensor and hydrophone data based on OTSM in this application. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to further clearly and completely describe the technical solutions in the embodiments of the present application. It should be noted that the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0020] In order to make the invention purpose, technical scheme and advantages of this application clearer, the technical scheme of the present invention is described clearly and completely in conjunction with the accompanying drawings and specific implementation schemes. It should be pointed out that for ordinary technicians in this field, several changes and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of this application.

[0021] The embodiments of the present application are further described in detail below in conjunction with the accompanying drawings: like Figure 1 As shown, this embodiment provides a method for aligning attitude sensor and hydrophone data based on OTSM, including: Step 1: Generate time series C Create a time series C with a time interval smaller than that of series A and B, so that the timestamps of A and B can find the closest matching point in C.

[0022] Define C(T n , tag1, attitude, tag2, hydrophone) protocol format, initialize all tag1 and tag2 values ​​to 0 to mark whether there is corresponding data. Select a time point TC from the time series C as the reference time for the current processing.

[0023] In one of the embodiments, the sampling frequency of the attitude sensor is set to 10 Hz to collect attitude angle and acceleration data under dynamic conditions to ensure the continuity of data changes; the sampling frequency of the hydrophone is set to 5 Hz to capture the changes in the sound wave signal in the underwater environment; the time interval of the time series C is set to 1 Hz to make its frequency higher than the attitude and hydrophone data sequences, ensuring that the closest attitude and sound wave data can be found for alignment.

[0024] Step 2: Insertion and propagation of pilot symbols Pilot symbols are inserted into the hydrophone signal. Pilot symbols are known and usually have good correlation characteristics, which facilitates signal detection and delay estimation at the receiving end. Pilot symbols are placed at specific positions in each frame so that the presence of pilot symbols can be detected at the receiving end through a sliding window search method. Pilot symbols reach the receiving end through different propagation paths, and each path will produce different delays due to multipath effects.

[0025] Step 3: Multipath Path Identification The sliding window method is used to identify the peak position of the pilot symbol in the DT (Delay-Time) domain to determine the delay on different paths. All paths are weighted averaged to calculate the final synchronization delay and perform delay compensation on the received hydrophone signal. , according to its signal strength , assign weight The delay after weighted average

[0026]

[0027] Step 4: Frequency Synchronization After time synchronization, the frequency offset in the signal needs to be compensated to achieve frequency consistency between the attitude sensor and hydrophone data. After time synchronization, the signal containing the pilot symbol is converted to the DS domain (Delay-Sequence) through the WHT (Walsh-Hadamard Transform). In the DS domain, the phase characteristics of the pilot signal are used for frequency synchronization. The pilot symbol provides a frequency reference in the DS domain for calculating the carrier frequency offset (CFO). The frequency offset in the signal is accurately estimated by matching the pilot signal. The estimated CFO value is used to compensate for the frequency drift in the signal to ensure that the frequency of the attitude data and the hydrophone data are aligned, thereby achieving higher synchronization accuracy.

[0028] Step 5: Insert the Gesture Sensor Data Find the closest sequence to T in sequence A C If a data point T1 matching the timestamp is found, the data is inserted into the corresponding position in the time series C.

[0029] Set tag1 = 1 to mark the C There is attitude sensor data at the time point; if no qualifying data point is found, tag1 = 0.

[0030] Step 6: Insert Hydrophone Data Similarly, find the closest sequence to T in sequence B. C If a data point T2 matching the timestamp is found, the data is inserted into the corresponding position in the time series C.

[0031] Set tag2 = 1 to mark the C There is hydrophone data at the time point; if no qualifying data point is found, tag2 = 0.

[0032] Step 7: Screen and generate alignment data sequence D Check each time point of time series C to find the time point that satisfies both tag1 = 1 and tag2 = 1, that is, find the synchronization point containing the attitude sensor and hydrophone data.

[0033] The data entries that meet the conditions are extracted to generate a new aligned data sequence D.

[0034] Step 8: Output data sequence D The data sequence D contains the aligned attitude sensor and hydrophone data, which can be used for subsequent analysis and processing.

[0035] Specific application scenarios of the method of this embodiment include Case 1 and Case 2.

[0036] Case 1: Used for marine dynamic environment monitoring In the marine environment, real-time monitoring of the dynamic changes of ocean currents and the acoustic noise characteristics of the surrounding environment is very important for marine research and maintenance of underwater facilities. The present invention realizes dynamic monitoring of complex underwater environments through high-precision data alignment of attitude sensors and hydrophones.

[0037] Experimental process: 1. Data collection: The attitude sensor is used to monitor the angle and displacement of the device underwater to evaluate the impact of the ocean current on the device's attitude. The hydrophone is used to collect acoustic signals in the surrounding environment to record the noise characteristics in the ocean. The data collection time is set to 10 minutes, the attitude sensor collects data at a frequency of 10Hz, and the hydrophone collects sound wave signals at a frequency of 5Hz.

[0038] 2 Insertion and propagation of pilot symbols: Pilot symbols are embedded in the collected signal of the hydrophone. The pilot symbols are used to help with subsequent time synchronization and frequency synchronization. The pilot symbols are placed at specific positions in the signal frame and propagate to the receiving end on different paths. These paths have different delays due to the multipath effect.

[0039] 3 Delay and frequency compensation: Delay compensation: The multipath weighted average method is used to perform weighted average on the delays of different paths to obtain the final synchronization delay, and the delay of the acoustic signal of the hydrophone is compensated.

[0040] Frequency synchronization: The signal is converted into the time delay-sequence domain (DS domain) through the Walsh-Hadamard transform (WHT), and the phase information of the pilot signal is used for frequency synchronization to compensate for the carrier frequency offset in the signal and ensure the frequency consistency of the attitude sensor and hydrophone data.

[0041] 4 Data alignment and analysis: The data of the attitude sensor and the compensated data of the hydrophone are aligned to generate an aligned data sequence D. The aligned data is used to analyze the impact of ocean currents on the device attitude, as well as the source and intensity changes of acoustic noise. Through further data processing, the data sequence D can calculate the correlation between the device attitude and environmental noise, thereby helping to understand the impact of ocean dynamic processes on the device.

[0042] Case 2: Used for accurate positioning of sound sources 1. Data collection: The attitude sensor is used to monitor the motion state of the positioning device underwater to ensure that the attitude information of the device is recorded in real time. The hydrophone is used to monitor the acoustic signal emitted by the underwater sound source and capture the various paths and signal changes during its propagation. The data collection time is set to 15 minutes, the sampling frequency of the attitude sensor is 10Hz, and the sampling frequency of the hydrophone is 5Hz.

[0043] 2 Insertion of pilot symbols: Specific pilot symbols are embedded in the sound source signal to identify the signal propagation path and perform time synchronization. Due to the complexity of the underwater environment, the sound source signal reaches the receiving end through multiple paths, and different paths produce different propagation delays.

[0044] 3 Multipath delay estimation and frequency synchronization: Delay estimation: In the DT (Delay-Time) domain, a sliding window is used to search for the position of the pilot symbol to determine the propagation delay of each path. The final delay compensation value is then calculated through weighted average calculation and the hydrophone data is compensated.

[0045] Frequency synchronization: The signal is converted into the DS domain using the WHT transform, and the carrier frequency offset is compensated by the phase characteristics of the pilot symbol to ensure the frequency consistency of the attitude data and the hydrophone data.

[0046] 4 Sound source localization: After delay and frequency compensation, an aligned data sequence D is generated. The aligned data is used in combination with the Doppler frequency shift algorithm to estimate the location of the sound source. The relative position of the sound source relative to the receiver is calculated by the delay difference of the pilot symbols received by multiple receivers.

[0047] The present application is a method for aligning attitude sensor and hydrophone data based on OTSM synchronization technology. Through the synchronization algorithm of the time axis and the delay axis, a pilot symbol is inserted into the hydrophone signal. The delay on different propagation paths is determined by finding the peak of the pilot signal to synchronize the data. The signal containing the pilot symbol is combined with the Walsh-Hadamard transform frequency compensation to achieve precise frequency alignment of multi-sensor data in complex environments, ensure the frequency alignment of attitude data and hydrophone data, and achieve higher synchronization accuracy.

Claims

1. A method for aligning attitude sensor and hydrophone data based on OTSM, characterized in that: include: Step S1, independently collecting attitude sensor data and hydrophone data to obtain attitude sensor data sequence A and hydrophone data sequence B; Step S2, creating a time series C, where the time interval of time series C is smaller than the time interval of sequence A and sequence B, so that the timestamps of sequence A and sequence B can find the closest matching point in C; Step S3, inserting a pilot symbol into the signal of the hydrophone, and placing the pilot symbol at a specific position of each frame; Step S4, using a sliding window search method to identify the peak position of the pilot symbol in the Delay-Time domain, thereby determining the delay of the signal on different paths and performing time synchronization on the data; Step S5, after completing the time synchronization, it is necessary to compensate for the frequency offset in the signal to achieve the consistency of the frequency between the attitude sensor and the hydrophone data; Step S6, find the closest T in the attitude sensor data sequence A and the hydrophone data sequence B. C The corresponding data points in sequence A and sequence B are inserted into the corresponding positions in time series C to update time series C; Step S7, checking each time point of the time series C, finding the synchronization point containing both the attitude sensor and the hydrophone data, extracting the data entries that meet the conditions, and generating a new aligned data sequence D; Step S8, outputting the aligned data sequence for subsequent analysis and processing.

2. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The attitude sensor data in step S1 includes attitude angle, time and acceleration, and the hydrophone data includes sound wave signal, frequency, sound intensity, waveform and time.

3. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The time interval of the time series C in step S2 is shorter than the time intervals of the sequence A and the sequence B, which includes: the sampling frequency of the attitude sensor is 10 Hz, the sampling frequency of the hydrophone is 5 Hz, and the time interval of the time series C is 1 Hz.

4. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The step S2 includes: defining a time series C(T n , tag1, attitude, tag2, hydrophone), select a time point T from the time series C C As the reference time for the current processing; where T n is time, attitude is attitude sensor data, hydrophone is hydrophone data, tag1 and tag2 represent attitude sensor data and hydrophone data tags respectively, and the initial values ​​of tag1 and tag2 are 0.

5. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The step S4 further includes: performing weighted average processing on the delays on different paths to calculate the final synchronization delay, and the calculation formula is: ,in, is the delay of the ith path , N is the number of different signal propagation paths, is the weight of different signal propagation paths; the received hydrophone signal is delayed compensated according to the weighted average delay, so that the attitude sensor and hydrophone data are synchronized in time.

6. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The step S5 comprises: after time synchronization, converting the signal containing the pilot symbol into the delay-sequence domain by Walsh-Hadamard transform, and performing frequency synchronization in the delay-sequence domain by using the phase characteristic of the pilot signal.

7. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 6, characterized in that: The frequency synchronization using the phase characteristic of the pilot signal in step S5 includes: calculating the carrier frequency offset CFO using the pilot symbol as a frequency reference, and using the estimated CFO value to compensate for the frequency drift in the signal to ensure that the frequency of the attitude data and the hydrophone data are aligned.

8. The method for aligning attitude sensor and hydrophone data based on OTSM according to claim 1, characterized in that: The step S6 specifically includes: Step S61, searching the sequence A for the closest T C If a data point T1 matching the timestamp is found, the data is inserted into the corresponding position in the time series C, and tag1=1 is set to mark the data point at T C There is attitude sensor data at the time point; if no data point that meets the conditions is found, then tag1=0; step S62, find the closest data point to T in sequence A C If a data point T2 matching the timestamp is found, the data is inserted into the corresponding position in the time series C, and tag2=1 is set to mark the data point at T C There is hydrophone data at the time point; if no qualifying data point is found, tag2=0.

9. A computer device comprising a memory, a processor, and program instructions stored in the memory and executable by the processor, wherein the processor executes the program instructions to implement the method according to any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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