Ultra-short baseline positioning precision detection method and system

Abstract

The invention discloses an FPGA + DSP architecture-based ultra-short baseline (USBL) positioning precision dynamic detection method and system, and aims to solve the technical problem that dynamic Doppler frequency shift and multipath interference cannot be effectively inhibited by traditional static calibration. According to the method, multi-domain cooperative anti-interference is achieved by designing an LFM-BPSK-PRN composite signal; an LFM synchronization head is used for establishing a time-frequency reference; BPSK speed measurement coding closed-loop feedback is used for compensating Doppler frequency offset in real time; a double-frequency pseudo-random noise (PRN) signal is used for suppressing multipath interference in a layered mode, shallow water short-delay resolution is improved through a high-frequency PRN, and long-distance anti-interference capacity is enhanced through a low-frequency PRN. The system adopts an FPGA + DSP cooperative processing architecture, an FPGA end completes signal generation, matched filtering and coarse time delay estimation, a DSP end executes Doppler compensation, phase difference calculation and error separation, and sound velocity and carrier disturbance are dynamically corrected in combination with a temperature and attitude sensor. The method supports on-line calibration in a laboratory pool or shallow sea environment, realizes high-precision detection that the distance measurement error is less than or equal to 0.3% slant distance and the direction measurement error is less than or equal to 0.3 degree in a scene that the flow velocity is less than or equal to 3m / s, improves the efficiency by more than 80% compared with a traditional method, and provides an efficient and reliable performance verification scheme for an underwater dynamic positioning system.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater acoustic positioning, and particularly relates to a method and system for detecting ranging and direction-finding accuracy of an ultra-short baseline (USBL) positioning system based on an FPGA+DSP architecture, which is particularly suitable for calibrating the dynamic performance of a USBL array in a laboratory environment or at the equipment factory stage. By designing an LFM-BPSK composite test signal, a matching filter for anti-multipath processing, and a real-time Doppler compensation mechanism, online high-precision detection of ranging error and direction-finding error is achieved, greatly improving the calibration efficiency and reliability under dynamic conditions. Background Art

[0002] The ultra-short baseline (USBL) positioning technology realizes high-precision positioning of underwater targets by measuring the phase difference and time delay difference of acoustic signals. Its nominal accuracy can reach a ranging error of 0.1% - 0.3% of the slant range and a direction-finding error of 0.1° - 0.3°. However, in an actual dynamic environment, affected by the Doppler frequency shift effect and shallow water multipath interference, the real error may be expanded to more than twice the nominal value, specifically manifested as follows:

[0003] Main reasons for ranging error: The Doppler frequency shift causes deviation in time delay estimation (error ≥ 0.5% when the flow velocity > 1 m / s), and multipath reflection leads to time delay extension (error ≥ 0.3 m in a shallow water environment);

[0004] Main reasons for direction-finding error: The attitude disturbance of the dynamic carrier (error ≥ 0.4° when the roll > 3°), and the phase difference drift caused by the Doppler effect.

[0005] Current laboratory calibration mostly relies on static pool tests, using standard acoustic beacons and high-precision mechanical devices (such as the rotating array method) to verify direction-finding / ranging errors. However, the static environment cannot simulate the Doppler frequency shift effect under dynamic flow velocities (such as a phase difference drift of ±5% when the flow velocity > 1 m / s), resulting in an overestimated direction-finding accuracy; although broadband signals such as linear frequency modulation (LFM) combined with time-domain amplitude screening technology can partially suppress multipath interference, there is still a lack of effective suppression means for short-time delay extension (time delay difference < 5 ms) caused by dense reflection paths in shallow water.

[0006] In addition, the traditional detection process needs to sequentially perform signal time-frequency domain feature extraction, multi-domain data fusion calculation, and off-line error item analysis, which has defects such as poor real-time performance (single detection takes more than 30 minutes) and insufficient adaptability to dynamic scenarios, and it is difficult to meet the rapid error assessment requirements in dynamic positioning scenarios.

[0007] To address the above problems, there is an urgent need to develop a detection system that integrates multipath suppression, real-time Doppler compensation, and lightweight hardware deployment. Without the need for deep-sea calibration facilities, high-precision and high-efficiency positioning performance calibration is achieved through dynamic signal simulation and online error tracing. Summary of the Invention

[0008] The object of the present invention is to provide a method and system for detecting the positioning accuracy of an ultra-short baseline USBL based on an FPGA+DSP architecture. By designing an anti-multipath composite signal and a real-time Doppler compensation mechanism, the technical problems of insufficient suppression of dynamic multipath interference and difficulty in separating ranging / direction-finding errors in the prior art are solved, and high-precision online calibration of an underwater positioning system is realized.

[0009] Method part:

[0010] 1. Using composite signal design, a linear frequency modulation (LFM) signal is used as the synchronization header at the signal transmitting end, combined with a velocity measurement coding signal (BPSK) and a two-segment pseudo-random noise (PRN) signal to respectively realize the delay reference, dynamic parameter pre-compensation, anti-multipath rough ranging, and high-precision ranging. At the signal reply end, reverse LFM synchronization is adopted, combined with the velocity measurement coding signal (BPSK) and a single-segment PRN signal to complete the verification of the round-trip delay and the suppression of residual multipath.

[0011] 2. Using the method of dynamic Doppler compensation, based on the closed-loop feedback of the velocity measurement coding signal, the frequency offset of the transmitted signal is corrected in real time to suppress the phase drift caused by Doppler. At the same time, the high-frequency and low-frequency PRN signals are combined for cooperative processing to expand the Doppler tolerance and improve the high-speed target tracking ability.

[0012] 3. In anti-multipath processing, a matching filtering method is used at the receiving end of the ultra-short baseline to detect the synchronization header of the transmitted signal. And using the frequency-domain separation characteristic of the dual-frequency PRN signal to distinguish the direct wave and the reflection path and suppress the short-delay multipath interference.

[0013] System part:

[0014] 1. Transmitting end hardware architecture:

[0015] Based on the FPGA, an anti-multipath composite signal is generated, and a high-precision time synchronization module is integrated to ensure the synchronization of multi-channel signals. The replied signal is collected to the DSP end, and the ranging error compensation effect is dynamically evaluated through the round-trip delay verification algorithm and the Doppler velocity compensation model.

[0016] 2. Receiving end real-time processing module

[0017] The FPGA is used to collect multi-channel composite signals in real time, and the inter-channel delay deviation is eliminated through the clock synchronization circuit. The synchronization header matching filtering and the rough estimation of the PRN signal delay are performed at the FPGA end, and the Doppler frequency offset compensation, phase difference calculation, and ranging / direction-finding error separation are completed at the DSP end.

[0018] 3. Dynamic error compensation module

[0019] Read the data from the temperature sensor and the attitude sensor, combine the multi-element phase difference calculation results, and dynamically compensate for errors. Utilize the frequency-domain anti-interference characteristics of the dual-frequency PRN signal to suppress the phase jitter caused by multipath, and output high-confidence azimuth / pitch angle estimation values.

[0020] 4. Ultra-short baseline array structure

[0021] The ultra-short baseline array adopts a four-element cross-shaped transducer layout, with the element spacing less than 1 / 2 of the wavelength corresponding to the center frequency of the working frequency band. The joint calculation of azimuth and pitch angles is realized through four orthogonally distributed elements, which can effectively suppress spatial aliasing and improve the azimuth calculation accuracy.

[0022] The beneficial effects of the present invention are as follows:

[0023] 1. Through the closed-loop feedback mechanism of the BPSK velocity measurement coding signal and the collaborative processing with the dual-frequency PRN, real-time frequency offset compensation is achieved in the scenario where the flow velocity ≤ 3 m / s, the ranging error is smaller, and the accuracy is improved compared with the traditional static calibration method.

[0024] 2. Adopt the dual-segment PRN signal (high-frequency anti-multipath coarse ranging + low-frequency high-precision ranging) and the matched filtering algorithm to suppress the dense reflection paths in shallow water, and the ranging confidence is improved.

[0025] 3. The FPGA + DSP collaborative architecture realizes the full-process processing of signal acquisition, filtering, and calculation, supports online real-time calibration, has less single detection time, and improves the efficiency compared with the traditional offline analysis.

[0026] 4. Combine the temperature sensor and the attitude sensor to dynamically compensate for the changes in the sound speed profile and the carrier perturbation, adapt to the laboratory, shallow sea, and dynamic navigation scenarios, and reduce the sea trial verification cost.

[0027] 5. The modular design supports direct deployment in a conventional experimental pool or production line without special anechoic facilities, reducing the hardware cost. Description of the drawings

[0028] Figure 1 It is a working schematic diagram of the ultra-short baseline positioning accuracy detection system of the present invention.

[0029] Figure 2 It is a working flow chart of the acoustic interrogator of the present invention.

[0030] Figure 3 It is a working flow chart of the acoustic transponder of the present invention.

[0031] Figure 4 It is a data frame structure diagram of the transmitted signal of the present invention.

[0032] Figure 5 It is a flow chart of the ultra-short baseline positioning accuracy detection of the present invention. Detailed implementation manners

[0033] The detection method and system of the present invention will be further described below in conjunction with the detailed implementation manners of the present invention and the accompanying drawings, so that the beneficial effects of the present invention will be further clarified.

[0034] As Figure 1 shown is a working schematic diagram of the ultra-short baseline positioning accuracy detection system. The system involves an underwater environment 9, an acoustic transponder 5, an acoustic interrogator 3, an ultra-short baseline array 4, a high-precision turntable 7, a computer 1, and a computer 8. The ultra-short baseline array 4 is composed of a four-element cross-shaped transducer array, and the element spacing is strictly less than half of the working frequency band wavelength. Its upper part is connected to the acoustic transponder 5 through a depth-setting rope and a communication cable 10, and the acoustic transponder 5 is connected to the computer 8 on the water surface through a depth-setting rope and a communication cable 6. At the same time, the ultra-short baseline array 4 is also rigidly connected to the high-precision turntable 7 on the water surface, and the ultra-short baseline array 4 can be rotated through the turntable 7. The acoustic interrogator 3 is connected to the computer 1 on the water surface through a depth-setting rope and a communication cable 2.

[0035] As Figure 2 shown is a working flowchart of the acoustic interrogator 3. This device is highly integrated with an FPGA+DSP cooperative processing system, a conditioning circuit module, and various communication interfaces on a single circuit board, and is encapsulated in a pressure-resistant sealed chamber, and is connected to the underwater acoustic transducer array through a waterproof connector. The FPGA generates a baseband waveform based on pre-stored signal source data (LFM-BPSK-PRN composite signal), generates a driving signal with a dead time through dual-channel complementary PWM modulation to avoid direct conduction damage of power switch devices. The signal output by the switching circuit is filtered by an LC filter network to remove high-frequency harmonics and restore a pure baseband waveform. The conditioned electrical signal is amplified by the transmitter power amplifier and fed into the underwater acoustic transducer to be converted into an acoustic wave signal and radiated into the underwater space. At the receiving end, the FPGA controls the ADC to receive the signal and then sends it to the DSP end through the UPP (Universal Parallel Port). The DSP end demodulates and calculates the data, and after obtaining the calculation result, it is transmitted to the computer 1 through the serial port for secondary verification.

[0036] As Figure 3The figure shows the workflow diagram of the acoustic transponder 5. This device consists of an FPGA+DSP cooperative processing system, a conditioning circuit module, and various communication interfaces, which are highly integrated on a single circuit board and encapsulated in a pressure-resistant sealed chamber. It is connected to the ultra-short baseline array 4 through a depth-fixed rope and a communication cable 10. The ultra-short baseline array 4 receives signals from the underwater acoustic channel, extracts the baseband signals through AD conversion and quadrature demodulation, and performs matched filtering on the LFM synchronization header of the signals in the FPGA. If the correlation peak exceeds the decision threshold, the signal transmission mechanism is triggered to transmit an inverse LFM+BPSK+PRN composite coded signal. The transmission principle is the same as that of the interrogator. At the same time, the collected data is sent to the DSP end through the UPP protocol, and the initial ranging and direction-finding data are calculated. Then, based on the frequency offset analysis of the BPSK signal to obtain the flow velocity, as well as the water temperature and attitude angle information read by the temperature and attitude sensors at the FPGA end, Doppler compensation, sound speed correction, and attitude angle compensation are performed on the preliminary results. Finally, the corrected high-precision ranging and direction-finding data are transmitted to the computer 8 through the communication cable 6. The ultra-short baseline array 4 can also be rotated by the high-precision turntable 7, and the actual rotation angle is compared with the calculated result to evaluate the confidence level of the direction-finding error.

[0037] As Figure 4 The figure shows the composite signal data frame structure designed for this system. Its core realizes the coordination of synchronization, speed measurement, and positioning functions through hierarchical anti-interference design. The transmitting-end signal (Figure a) uses an LFM synchronization header with a center frequency of 18 kHz and a linearly increasing bandwidth of 4 kHz as the time-domain reference, and utilizes the wideband frequency modulation characteristic to resist the Doppler frequency offset. Subsequently, a guard interval is inserted to isolate the inter-symbol interference, and then a 93-symbol 18 kHz single-frequency BPSK speed measurement coded signal is connected. The speed pre-compensation parameter is embedded through phase modulation to support closed-loop Doppler correction. On this basis, a dual-frequency PRN positioning signal is deployed. Among them, the 18 kHz low-frequency PRN (127-symbol single-frequency) suppresses the long-distance multipath interference, and the 20 kHz high-frequency PRN (127-symbol single-frequency) improves the shallow water delay resolution by 40% through the short-wavelength characteristic. The two are hierarchically isolated through the guard interval to form an anti-interference gradient. The receiving-end signal (Figure b) uses an inverse LFM synchronization header with a center frequency of 18 kHz and a linearly decreasing bandwidth of 4 kHz, compensates for the two-way propagation path difference through time-frequency symmetry, retains the BPSK speed measurement coding to achieve dynamic parameter feedback, and combines a single-segment 18 kHz PRN signal to complete the closed-loop time delay verification. This architecture realizes the dynamic balance of synchronization accuracy, Doppler robustness, and multipath suppression ability in a complex underwater acoustic channel through the frequency-domain division of labor (low-frequency anti-interference / high-frequency accuracy improvement) and time-domain coordination (guard interval hierarchical isolation) mechanisms.

[0038] A method for detecting the positioning accuracy of an ultra-short baseline, using the above-mentioned ultra-short baseline positioning accuracy detection system, includes the following steps:

[0039] Step 1: Deploy the detection system in a laboratory pool or a shallow sea test site. Verify the establishment of a two-way communication link between the computer 1 and the acoustic interrogator 3, and between the computer 8 and the acoustic transponder 5 to complete the device handshake protocol test. Send a single signal transmission instruction from the computer 1 to the acoustic interrogator 3, receive the signal strength feedback through the acoustic transponder 5, and dynamically configure the gain parameters of the underwater acoustic transducer to eliminate signal clipping. Subsequently, perform the initial direction finding and ranging operations based on the Figure 5 detection process shown to verify the response correctness of the core functional modules of the system.

[0040] Step 2: Adjust the relative distance between the acoustic interrogator 3 and the ultra-short baseline array 4. Measure the minimum effective operating distance at which the received signal is distortion-free in the low-power mode, and synchronously record the ranging error and the residual of the direction finding angle at this distance. If testing in a shallow sea environment, further switch to the high-power mode, measure the maximum effective operating distance and its corresponding ranging accuracy and direction finding accuracy, and quickly generate the relationship curve between the operating distance and accuracy through the real-time data processing module to quantify the positioning performance boundary of the system within the dynamic range.

[0041] Step 3: Control the high-precision turntable 7 to rotate the ultra-short baseline array 4 at a preset angular step (such as 0.1°), and perform a signal transmission and reception process after each rotation. The four-element cross-shaped ultra-short baseline array 4 synchronously receives signals through four orthogonally distributed transducers, uses the spatial characteristics of the short baseline to enhance the ability to distinguish multi-path, and provides a stable phase difference input for the rotation calibration of the high-precision turntable 7. By comparing the actual rotation angle fed back by the turntable encoder with the azimuth angle calculated by the system, calculate the absolute direction finding error and establish a calibration database of the direction finding error varying with the angle.

[0042] Step 4: First, control the acoustic interrogator 3 to approach or move away from the ultra-short baseline array 4 radially at a preset speed (v ≤ 3 m / s). Continuously perform signal transmission and reception during the movement, and observe the correction effect of the Doppler frequency shift compensation mechanism on the ranging result; then, maintain a fixed distance and perform a tangential uniform motion (v ≤ 3 m / s), and record the fluctuation amplitude of the azimuth angle solution value in real time. By comparing the standard deviation of the ranging error and the jitter range of the direction finding angle before and after compensation, verify the anti-Doppler performance under dynamic conditions.

[0043] Step 5: Based on the test data sets in Steps 2 to 4, respectively construct a ranging error distribution model and a spatial distribution matrix of the direction finding error. Determine the positioning accuracy index of the system within the nominal operating range through the confidence interval analysis method (such as 95% confidence level): When the ranging error ≤ 0.3% of the slant range and the direction finding error ≤ 0.3°, it is determined that the system meets the dynamic calibration requirements, and a calibration certificate containing error compensation parameters is generated.

[0044] Through the design of LFM-BPSK-PRN composite signals, Doppler closed-loop compensation and two-way verification mechanism, combined with the hardware co-processing of FPGA+DSP, the present invention realizes high-precision real-time ranging and direction finding that resists multipath and frequency offset in a dynamic environment, greatly improving the calibration efficiency and reliability.

[0045] The above description is an explanation of the present invention, not a limitation of the invention. For the scope defined by the present invention, refer to the claims. Any form of modification can be made within the protection scope of the present invention.

Claims

1. An ultra-short baseline positioning accuracy detection system, characterized in that: An underwater environment (9), applicable to laboratory pool or shallow sea test scenarios; an ultra-short baseline array (4), adopting a four-element cross-shaped array structure; an acoustic transponder (5), connected to the ultra-short array (4) through a depth-fixed rope and a communication cable (10); an acoustic interrogator (3), connected to a surface computer (1) through a depth-fixed rope and a communication cable (2); a high-precision turntable (7), rigidly connected to the ultra-short baseline array (4) to provide an azimuth reference; a computer (1) and a computer (8), respectively used for controlling the signal transceiver and data processing of the acoustic interrogator (3) and the acoustic transponder (5).

2. The ultra-short baseline positioning accuracy detection system according to claim 1, characterized in that: The acoustic interrogator (3) includes an FPGA+DSP cooperative processing module, a conditioning circuit module and a pressure-resistant sealed cabin; the FPGA module pre-stores the data of the LFM-BPSK-PRN composite coding signal source, generates a driving signal with dead time through dual-channel complementary PWM modulation, filters out high-frequency harmonics through an LC filter network, amplifies the power by a transmitter and feeds it into the underwater acoustic transceiver combined transducer array; at the receiving end, the FPGA controls the ADC to collect the echo signal, transmits it to the DSP end through the UPP interface for Doppler compensation and error calculation, and finally outputs it to the computer (1) through a serial port for secondary verification.

3. The ultra-short baseline positioning accuracy detection system according to claim 1, wherein: The acoustic transponder (5) integrates an FPGA+DSP cooperative processing module, a temperature sensor and an attitude sensor; the FPGA end performs matched filtering detection on the LFM synchronization header of the received signal, triggering the reverse LFM-BPSK-PRN signal transmission mechanism; the DSP end combines the frequency offset analysis of the BPSK speed measurement coding, the water temperature data collected by the temperature sensor and the angle information of the attitude sensor to perform Doppler compensation, sound speed correction and attitude disturbance correction on the ranging / direction finding results, and outputs high-precision positioning data to the computer (8).

4. The ultra-short baseline positioning accuracy detection system according to claim 1, wherein: The ultra-short baseline array (4) includes a four-element cross-shaped transducer array, and the element spacing is less than 1 / 2 wavelength; the array realizes the rotation control with a step size of 0.1° in the horizontal plane through the high-precision turntable (7), and the turntable encoder feeds back the actual rotation angle to the computer (8) for comparison with the system-solved azimuth angle for direction finding error comparison.

5. The ultra-short baseline positioning accuracy detection system according to claim 1, characterized in that: The composite signal includes a hierarchical anti-interference structure. The signal frames at the transmitting end are in sequence: an LFM synchronization header with a center frequency of 18 kHz and a bandwidth of 4 kHz; a guard interval; a 93-symbol BPSK speed measurement coding; a dual-frequency PRN positioning signal (18 kHz low-frequency band and 20 kHz high-frequency band); the signal frames at the transmitting-back end are in sequence: a reverse LFM synchronization header, a BPSK speed measurement coding and a single-segment PRN verification signal, suppressing multipath interference through frequency-domain division and time-domain cooperation.

6. A method for detecting the positioning accuracy of an ultra-short baseline, using the above ultra-short baseline positioning accuracy detection system, characterized in that, Including the following steps: Step 1: Deploy the detection system in a laboratory pool or a shallow sea test site. Verify the establishment of a two-way communication link between computer 1 and the acoustic interrogator 3, and between computer 8 and the acoustic transponder 5 to complete the device handshake protocol test. Send a single signal transmission instruction from computer 1 to the acoustic interrogator 3, receive the signal strength feedback through the acoustic transponder 5, and dynamically configure the gain parameters of the underwater acoustic transducer to eliminate signal clipping. Subsequently, perform the initial direction finding and ranging operations based on the detection process shown in Figure 5 to verify the response correctness of the core functional modules of the system. Step 2: Adjust the relative distance between the acoustic interrogator 3 and the ultra-short baseline array 4. Measure the minimum effective operating range where the received signal is distortion-free in the low power mode, and synchronously record the ranging error and the residual direction finding angle of this range. If testing in a shallow sea environment, further switch to the high power mode, measure the maximum effective operating range and its corresponding ranging accuracy and direction finding accuracy, and quickly generate the relationship curve of operating range - accuracy through the real-time data processing module to quantify the positioning performance boundary of the system within the dynamic range. Step 3: Control the high-precision turntable 7 to rotate the ultra-short baseline array 4 at a preset angular step (such as 0.1°), and perform a signal transmission and reception process after each rotation. Calculate the absolute direction finding error by comparing the actual rotation angle fed back by the turntable encoder with the azimuth angle calculated by the system, and establish a calibration database of the direction finding error varying with the angle. Step 4: First, control the acoustic interrogator 3 to approach or move away from the ultra-short baseline array 4 along the radial direction at a preset speed (≤3 m / s). Continuously perform signal transmission and reception during the movement to observe the correction effect of the Doppler frequency shift compensation mechanism on the ranging result; then, keep a fixed distance and perform a tangential uniform motion (v≤3 m / s), and record the fluctuation amplitude of the azimuth angle calculation value in real time. Verify the anti-Doppler performance under dynamic conditions by comparing the standard deviation of the ranging error and the jitter range of the direction finding angle before and after compensation. Step 5: Based on the test data sets in Steps 2 to 4, respectively construct a ranging error distribution model and a spatial distribution matrix of the direction finding error. Determine the positioning accuracy index of the system within the nominal operating range through the confidence interval analysis method (such as 95% confidence level): When the ranging error ≤ 0.3% of the slant range and the direction finding error ≤ 0.3°, it is determined that the system meets the dynamic calibration requirements, and a calibration certificate containing error compensation parameters is generated.

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