Positioning method, system and device based on time delay and Doppler joint estimation and medium

Abstract

The invention provides a positioning method, system and device based on time delay and Doppler joint estimation and a medium, the method constructs an impulse response model with a broadband underwater sound multipath channel based on a bistatic measurement system, considers multipath factors, and reduces precision reduction of time delay and Doppler joint estimation caused by ignoring the multipath factors; and meanwhile, through time delay and Doppler joint estimation, the problem that the correlation between time delay and Doppler cannot be calculated in the prior art is solved, and the precision of calculating the time delay and Doppler covariance matrix is improved, so that the precision of positioning the underwater target is improved.

Description

Technical Field

[0001] This invention belongs to the field of signal processing technology, specifically relating to a positioning method, system, device, and medium based on joint estimation of time delay and Doppler. Background Technology

[0002] Bistatic positioning aims to obtain the relevant location information of a target through the detection and computation capabilities of a bistatic system. Bistatic underwater target positioning technology can provide theoretical basis and technical support for applications such as underwater safe navigation, rapid salvage and rescue, anti-submarine warfare, and marine resource development. Bistatic target positioning mainly relies on constructing a corresponding positioning model based on various measured physical quantities (such as bearing, time delay, and Doppler shift), and then using different types of positioning methods to obtain the target's position.

[0003] To fully utilize the acquired measurement information, multiple different physical quantities are typically combined for target localization. Due to the significant Doppler effect in the underwater environment, time delay and Doppler factors have been widely used for bistatic underwater target localization. When using time delay and Doppler for bistatic target localization, the localization accuracy is closely related to the measurement accuracy of time delay and Doppler. The measurement accuracy of these two physical quantities is usually characterized by the covariance matrix. Therefore, to accurately evaluate the performance of target localization, the precise covariance matrix of the two measurements must be obtained. Traditional methods for calculating the measurement covariance matrix of time delay and Doppler usually assume that the two random variables are independent, simplifying the calculation of the covariance matrix to calculating the variance of the two random variables, and then using empirical methods to calculate the correlated variance. However, the time delay and Doppler estimated from the same detection signal are strongly correlated, and it is difficult to calculate the precise variance using empirical methods. Furthermore, underwater multipath effects are another important factor affecting the accuracy of covariance matrix calculation.

[0004] The strong multipath effect of underwater acoustic channels and the strong correlation between time delay and Doppler make it difficult to obtain accurate covariance matrix of multidimensional information. Inaccurate measurement information will lead to a decrease in positioning performance. Therefore, this application anticipates a method that can accurately calculate the covariance matrix of time delay and Doppler and perform target positioning. Summary of the Invention

[0005] To overcome the problem that existing technologies cannot accurately calculate the covariance matrix of time delay and Doppler, thus making it impossible to accurately locate underwater targets, this invention provides a positioning method, system, device, and medium based on joint estimation of time delay and Doppler.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] In a first aspect, embodiments of this disclosure provide a localization method based on joint estimation of time delay and Doppler, comprising the following steps:

[0008] Step S1: Construct an impulse response model with broadband underwater acoustic multipath channels based on a bistatic measurement system;

[0009] Step S2: Based on the impulse response model and the detection signal, obtain the received signal;

[0010] Step S3: The detection signal adopts a linear frequency modulated signal, and the lower bound of the channel parameter estimation is obtained based on the received signal;

[0011] Step S4: Based on the lower bound of the channel parameter estimation, obtain the lower bound of the parameters related to the time delay and Doppler factor;

[0012] Step S5: Based on the Cramer-Rao lower bound of the time delay and Doppler factor related parameters, the chain rule is used to obtain the Cramer-Rao lower bound of the time delay and Doppler factor. The Cramer-Rao lower bound of the time delay and Doppler factor is used as the covariance matrix of the time delay and Doppler factor, and the target is located based on the covariance matrix.

[0013] Furthermore, the bistatic measurement system includes at least a transmitting base station and a receiving base station. The transmitting base station is used to transmit detection signals, and the receiving base station is used to receive the echo signals of the detection signals transmitted by the transmitting base station after being reflected by the target.

[0014] The echo signal is analyzed to include at least: time delay measurement and Doppler factor measurement.

[0015] Furthermore, constructing the impulse response model includes the following steps:

[0016] Construct the initial impulse response model:

[0017] ;

[0018] In the formula, Describing the Dirac function, It is the total number of paths. and They are the first The time-varying amplitude and time-varying delay of each path;

[0019] In a short period of time, assuming the time-varying amplitude of the path If it is a constant, then the time-varying amplitude of the path For time-independent parameters Then time-varying delay An approximate expression is:

[0020] ;

[0021] In the formula, yes Zero-order Taylor expansion; For the first The rate of change of path delay;

[0022] The impulse response model is then:

[0023] .

[0024] Furthermore, when the received signal is obtained in step S2, the following steps are included:

[0025] When the transmitted detection signal is At that time, the received signal without considering noise include:

[0026] ;

[0027] In the formula, For delay Differential calculations;

[0028] definition and Then the received signal without considering noise Simplified to:

[0029] ;

[0030] In the formula, and They are the first Doppler factor and time delay for each path.

[0031] Furthermore, if the detection signal in step S3 is a linear frequency modulated signal, then the received signal... include:

[0032] ;

[0033] In the formula, It is additive Gaussian noise; For a constant linear frequency modulated signal, t is the complex representation; t is time. ; For the number of paths, The path contains One unknown parameter, The set of unknown parameters yields a vector form of the unknown parameters: The elements in the vector form of the unknown parameters are represented as ;and:

[0034] ;

[0035] In the formula, ; ; and These are the amplitude, starting frequency, modulation slope, and initial phase of the linear frequency modulated signal, respectively.

[0036] If the sampling frequency is Hz, resulting in a sampling period of Then the vector form of the unknown parameters The Fisher information matrix is ​​represented as:

[0037] ;

[0038] In the formula, For the matrix blocks of the Fisher information matrix:

[0039] ;

[0040] In the formula, and The value range is 1 to , The standard deviation of the noise; This is the operation of extracting the real part; n is the sampling number; The number of samples; This is a conjugate operation;

[0041] ;

[0042] Based on the Fisher information matrix representation, the channel parameter estimation is obtained using Cramerro. for:

[0043] .

[0044] Furthermore, the parameters related to time delay and Doppler factor in step S4 are as follows: ;

[0045] Vector form of unknown parameters Fisher information matrix representation Block representation:

[0046] ;

[0047] In the formula, ; ; ; ;

[0048] The parameters related to time delay and Doppler factor are obtained using the block matrix inversion theorem. Clamelo's Lower Realm :

[0049] .

[0050] Furthermore, when obtaining the lower bound of Cramérault as described in step S5, the vector parameters are defined. Then the lower bound of the time delay and Doppler factor is Clamer-Rao. for:

[0051] ;

[0052] In the formula, .

[0053] In a second aspect, embodiments of this disclosure provide a positioning system based on joint time delay and Doppler estimation, comprising:

[0054] The initialization unit is configured to: construct an impulse response model with a broadband underwater acoustic multipath channel based on a bistatic measurement system;

[0055] The first processing unit is configured to: obtain the received signal based on the impulse response model and the detection signal;

[0056] The second processing unit is configured to: use a linear frequency modulated signal for the detection signal, and obtain the Cramer-Rao lower bound of the channel parameter estimation based on the received signal;

[0057] The third processing unit is configured to: obtain the lower bound of the parameters related to the time delay and the Doppler factor based on the lower bound of the channel parameter estimation;

[0058] The output unit is configured to: obtain the lower bounds of the time delay and Doppler factor based on the Cramer-Rao lower bounds of the time delay and Doppler factor using the chain rule; use the lower bounds of the time delay and Doppler factor as the covariance matrix of the time delay and Doppler factor; and perform target localization based on the covariance matrix.

[0059] In a third aspect, embodiments of this disclosure provide an electronic device, characterized in that the electronic device comprises:

[0060] At least one processor; and,

[0061] The memory is communicatively connected to the at least one processor; wherein,

[0062] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the localization method based on time delay and Doppler joint estimation.

[0063] In a fourth aspect, embodiments of this disclosure provide a non-transitory computer-readable storage medium, characterized in that the non-transitory computer-readable storage medium stores computer instructions for causing the computer to execute the positioning method based on time delay and Doppler joint estimation.

[0064] Compared with the prior art, the present invention has the following beneficial technical effects:

[0065] This application provides a positioning method, system, device, and medium based on joint estimation of time delay and Doppler. The method constructs an impulse response model with a broadband underwater acoustic multipath channel based on a bistatic measurement system, taking into account multipath factors and reducing the decrease in accuracy of joint estimation of time delay and Doppler caused by ignoring multipath factors. At the same time, by using joint estimation of time delay and Doppler, it solves the problem in existing related technologies that cannot calculate the correlation between time delay and Doppler, improves the accuracy of calculating the covariance matrix of time delay and Doppler, and thus improves the accuracy of locating underwater targets. Attached Figure Description

[0066] Figure 1 A flowchart of a localization method based on joint time delay and Doppler estimation according to an embodiment of the present disclosure is shown;

[0067] Figure 2 A schematic diagram of a bistatic measurement system according to an embodiment of the present disclosure is shown;

[0068] Figure 3 The diagram shows a comparison of the estimated variances of time delay and Doppler factor obtained using different methods under different noise levels according to embodiments of this disclosure.

[0069] Figure 4 This invention discloses a comparative graph showing the impact of multipath effect on the bistatic target position estimation performance as the measurement noise level changes in an embodiment of the present disclosure.

[0070] Figure 5 This invention discloses a comparative graph showing the impact of multipath effect on the velocity estimation performance of bistatic targets as the measurement noise level changes in an embodiment of this disclosure.

[0071] Figure 6 A comparison diagram showing the impact of the proposed method and the empirical method on the performance of bistatic target location estimation in the embodiments of this disclosure is shown.

[0072] Figure 7 A comparison diagram showing the impact of the proposed method and the empirical method on the velocity estimation performance of bistatic targets in the embodiments of this disclosure is shown.

[0073] Figure 8 A diagram of an apparatus for a localization method based on joint time delay and Doppler estimation according to an embodiment of the present disclosure is shown. Detailed Implementation

[0074] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0075] Figure 1 The following is a flowchart 100 of a localization method based on joint time delay and Doppler estimation in an embodiment of this disclosure, as shown below. Figure 1 As shown, it includes the following steps:

[0076] In step S101, an impulse response model with a broadband underwater acoustic multipath channel is constructed based on a bistatic measurement system.

[0077] Specifically Figure 2 A schematic diagram of a bistatic measurement system according to an embodiment of the present disclosure is shown. The bistatic measurement system includes at least a transmitting base station and a receiving base station. The transmitting base station is used to transmit a detection signal, and the receiving base station is used to receive the echo signal of the detection signal transmitted by the transmitting base station after being reflected by the target.

[0078] The echo signal is analyzed to include at least: time delay measurement and Doppler factor measurement.

[0079] Specifically, in order to obtain accurate time delay and Doppler measurements, considering the long delay and multipath characteristics of the underwater environment, the impulse response model is constructed, including the following steps:

[0080] Construct the initial impulse response model:

[0081] ;

[0082] In the formula, Describing the Dirac function, It is the total number of paths. and They are the first The time-varying amplitude and time-varying delay of each path;

[0083] The variation in time delay is primarily caused by the relative motion of the transmitting base station, receiving base station, and target, while the variation in path amplitude is due to the time-varying marine environment. In a short time, assuming the path's time-varying amplitude... If it is a constant, then the time-varying amplitude of the path For time-independent parameters Then time-varying delay An approximate expression is:

[0084] ;

[0085] In the formula, yes Zero-order Taylor expansion; For the first The rate of change of path delay;

[0086] The impulse response model is then:

[0087] .

[0088] Next, proceed to step S102.

[0089] In step S102, the initial received signal is obtained based on the impulse response model and the detection signal.

[0090] Specifically, when obtaining the initial received signal in step S102, the following steps are included:

[0091] When the transmitted detection signal is At that time, the received signal without considering noise include:

[0092] ;

[0093] In the formula, For delay Differential calculations;

[0094] definition and Then the received signal without considering noise Simplified to:

[0095] ;

[0096] In the formula, and They are the first Doppler factor and time delay for each path.

[0097] Next, proceed to step S103.

[0098] In step S103, the detection signal is a linear frequency modulated signal, and the lower bound of the channel parameter estimation is obtained based on the received signal.

[0099] Specifically, in step S103, the detection signal is a linear frequency modulated signal, and the received signal includes:

[0100] ;

[0101] In the formula, It is additive Gaussian noise For a constant linear frequency modulated signal, t is the complex representation; t is time. ; For the number of paths, The path contains One unknown parameter, The set of unknown parameters yields a vector form of the unknown parameters: The elements in the vector form of the unknown parameters are represented as ;and:

[0102] ;

[0103] In the formula, ; ; and These are the amplitude, starting frequency, modulation slope, and initial phase of the linear frequency modulated signal, respectively.

[0104] If the sampling frequency is Hz, resulting in a sampling period of Then the vector form of the unknown parameters The Fisher information matrix is ​​represented as:

[0105] ;

[0106] In the formula: For the Fisher information matrix blocks;

[0107] ;

[0108] In the formula, and The value range is 1 to , The standard deviation of the noise; This is for the operation of taking the real part; The sampling sequence number; The number of samples; This is a conjugate operation;

[0109] ;

[0110] Based on the Fisher information matrix representation, the channel parameter estimation is obtained using Cramerro. for:

[0111] .

[0112] Next, proceed to step S104.

[0113] At step S104, based on the lower bound of the Cramer-Rao parameter estimation, the lower bound of the parameters related to the delay and Doppler factor is obtained.

[0114] Specifically, the parameters related to time delay and Doppler factor in step S104 are: ;

[0115] Vector form of unknown parameters Fisher information matrix representation Block representation:

[0116] ;

[0117] In the formula, ; ; ; ;

[0118] The parameters related to time delay and Doppler factor are obtained using the block matrix inversion theorem. The initial Clameros lower bound :

[0119] .

[0120] Next, proceed to step S105.

[0121] In step S105, based on the lower bound of the Cramer-Rao parameter related to the time delay and Doppler factor, the chain rule is used to obtain the lower bound of the Cramer-Rao parameter related to the time delay and Doppler factor, which is used as the covariance matrix of the time delay and Doppler factor, and the target is located based on the covariance matrix.

[0122] Specifically, when obtaining the optimized Cramer-Rao lower bound as described in step S105, the vector parameters are defined. Then the lower bound of the time delay and Doppler factor is Clamer-Rao. for:

[0123] ;

[0124] In the formula, .

[0125] When the signal-to-noise ratio is high, the Cramero lower bound of the time delay and Doppler factor is approximately equal to the covariance matrix of the time delay and Doppler factor. Target localization based on the covariance matrix is ​​a common technique in this field.

[0126] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail with reference to the embodiments.

[0127] Consider the following moving target localization scenario, at time... The locations of the transmitting base station and the receiving base station are respectively m and m; the target is located m, speed is m / s.

[0128] The parameters for the Linear Frequency Modulation (LFM) probe signal are set as follows: bandwidth is... Hz, bandwidth is ms, starting frequency is Hz, sampling frequency is Hz.

[0129] Consider a multipath channel with 5 paths, where path 1 is a direct path. The time delay, Doppler factor and amplitude parameters for each path are set as shown in Table 1.

[0130] surface Multipath channel parameter settings

[0131] Channel parameters Path 1 Path 2 Path 3 Path 4 Path 5 Latency (s) 2.648 2.648 2.648 2.648 2.648 Doppler factor 0.993 0.993 0.993 0.993 0.993 Amplitude 1.00 0.95 0.90 0.85 0.80

[0132] In the first simulation experiment, the effectiveness of the joint estimation method based on time delay and Doppler factor proposed in this embodiment is evaluated. Figure 3 The diagram shows a comparison of the estimated variances of time delay and Doppler factor obtained using different methods under different noise levels according to embodiments of this disclosure. It can be seen that, when considering the multipath component (MPC), the estimated time delay variance and Doppler factor variance of the method proposed in this embodiment are close to those estimated by the FrFT method. This demonstrates the accuracy of the proposed method in estimating the covariance of time delay and Doppler factor. Furthermore, from... Figure 3 As can be seen, when the method proposed in this embodiment ignores MPC, the obtained time delay and Doppler factor variance are far from the results obtained by the method proposed in this embodiment considering MPC. This shows that ignoring MPC will lead to inaccurate calculation of time delay and Doppler factor covariance.

[0133] Next, this embodiment verifies the impact of the accuracy of the covariance matrix of time delay and Doppler factor on the positioning accuracy of bistatic targets. Since the noise levels of the transmitting and receiving base stations are different and variable when receiving echo signals, this embodiment sets the noise levels of the transmitting and receiving base stations accordingly. and It changes from 0.1 to 1. Figure 4 and Figure 5 The effects of multipath effects on the estimation performance of bistatic target position and velocity as the measurement noise level changes are shown. It can be seen that the estimation errors of target position and velocity increase with increasing measurement noise level, and the multipath effect leads to an increase in these errors. This result demonstrates that ignoring the multipath effect results in inaccurate measurement covariance of TOA and Doppler factor, ultimately leading to inaccurate bistatic target localization.

[0134] To further verify the effectiveness of the method proposed in this embodiment, it is compared with existing related empirical methods. It is assumed that empirical methods can obtain accurate time delay and Doppler factor variances, and that the time delay and Doppler factor measurements are independent of each other. Figure 6 and Figure 7 The impact of using the empirical method and the method proposed in this embodiment on the performance of bistatic target position and velocity estimation is shown respectively. It can be seen that although the traditional empirical method is assumed to obtain accurate time delay and Doppler factor variance, ignoring the strong correlation between time delay and Doppler factor leads to inaccurate covariance calculation, resulting in a decrease in the accuracy of target position and velocity estimation. The method proposed in this embodiment has higher accuracy.

[0135] A second embodiment of the present invention also provides a positioning system based on joint estimation of time delay and Doppler, comprising:

[0136] The initialization unit is configured to: construct an impulse response model with a broadband underwater acoustic multipath channel based on a bistatic measurement system;

[0137] The first processing unit is configured to: obtain an initial received signal based on the impulse response model and the known detection signal;

[0138] The second processing unit is configured to: adjust the known detection signal into a linear frequency modulated signal, optimize the initial received signal to obtain an optimized initial signal, and obtain the Cramero signal for channel parameter estimation based on the optimized initial signal;

[0139] The third processing unit is configured to: obtain an initial lower bound of the Cramer-Rao parameter related to the time delay and Doppler factor based on the Cramer-Rao parameter estimation of the channel parameters;

[0140] The output unit is configured to: obtain optimized Cramer-Rao lower bounds for time delay and Doppler factor based on the initial Cramer-Rao lower bound using the chain rule, use the optimized Cramer-Rao lower bounds as the covariance matrix of time delay and Doppler factor, and perform target localization based on the covariance matrix.

[0141] The third embodiment of the present invention also provides an electronic device, the electronic device comprising:

[0142] At least one processor; and,

[0143] The memory is communicatively connected to the at least one processor; wherein,

[0144] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the localization method based on time delay and Doppler joint estimation of any of the foregoing embodiments.

[0145] The fourth embodiment of the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the localization method based on time delay and Doppler joint estimation as described in any of the foregoing embodiments.

[0146] The fifth embodiment of the present invention also provides a computer program product, which includes a computing program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions that, when executed by a computer, cause the computer to perform the localization method based on time delay and Doppler joint estimation of any of the foregoing embodiments.

[0147] Figure 8 The illustration shows a method or device 1000 implementing an embodiment of the present invention. In some embodiments, more or fewer devices may be included than illustrated. In some embodiments, it may be implemented using a single or multiple devices. In some embodiments, it may be implemented using cloud-based or distributed devices.

[0148] like Figure 8 As shown, device 1000 includes a processor 1001 for performing various appropriate operations and processes based on programs and / or data stored in read-only memory (ROM) 1002 or programs and / or data loaded from storage portion 1008 into random access memory (RAM) 1003. Processor 1001 may be a multi-core processor or may contain multiple processors. In some embodiments, processor 1001 may include a general-purpose main processor and one or more special coprocessors, such as a central processing unit (CPU), graphics processing unit (GPU), neural network processor (NPU), digital signal processor (DSP), etc. Various programs and data required for the operation of device 1000 are also stored in RAM 1003. Processor 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0149] The processor and memory described above are used together to execute programs stored in the memory. When the program is executed by a computer, it can implement the methods, steps, or functions described in the above embodiments.

[0150] The following components are connected to I / O interface 1005: an input section 1006 including a keyboard, mouse, touchscreen, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to I / O interface 1005 as needed. A removable medium 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 1010 as needed so that computer programs read from it can be installed into storage section 1008 as needed. Figure 8 The diagram only shows a portion of the components and does not imply that the device 1000 only includes... Figure 8 The components shown.

[0151] The systems, devices, modules, or units described in the above embodiments can be implemented by a computer or its associated components. The computer may be, for example, a mobile terminal, smartphone, personal computer, laptop computer, in-vehicle human-machine interface device, personal digital assistant, media player, navigation device, game console, tablet computer, wearable device, smart TV, Internet of Things system, smart home, industrial computer, server, or a combination thereof.

[0152] Although not shown, in this embodiment of the invention, a computer-readable storage medium is provided having a computer program / instructions stored thereon, which, when executed by a processor, implements the localization method based on joint time delay and Doppler estimation as described in the embodiment.

[0153] Storage media in embodiments of the present invention include articles that are permanent and non-permanent, removable and non-removable, capable of storing information by any method or technology. Examples of storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0154] Although not shown, embodiments of the present invention also provide a computer program product, including: a computer program / instructions that, when executed by a processor, implement the localization method based on joint time delay and Doppler estimation described in the embodiments.

[0155] The methods, programs, systems, apparatuses, etc., in embodiments of the present invention can be executed or implemented in one or more networked computers, or practiced in a distributed computing environment. In the embodiments of this specification, in these distributed computing environments, tasks can be performed by remote processing devices connected via a communication network.

Claims

1. A positioning method based on joint estimation of time delay and Doppler, characterized in that, Includes the following steps: Step S1: Construct an impulse response model with broadband underwater acoustic multipath channels based on a bistatic measurement system; Step S2: Based on the impulse response model and the detection signal, obtain the received signal; Step S3: The detection signal adopts a linear frequency modulated signal, and the lower bound of the channel parameter estimation is obtained based on the received signal; Step S4: Based on the lower bound of the channel parameter estimation, obtain the lower bound of the parameters related to the time delay and Doppler factor; Step S5: Based on the Cramer-Rao lower bound of the time delay and Doppler factor related parameters, the chain rule is used to obtain the Cramer-Rao lower bound of the time delay and Doppler factor. The Cramer-Rao lower bound of the time delay and Doppler factor is used as the covariance matrix of the time delay and Doppler factor, and the target is located based on the covariance matrix.

2. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, The bistatic measurement system includes at least a transmitting base station and a receiving base station. The transmitting base station is used to transmit detection signals, and the receiving base station is used to receive the echo signals of the detection signals transmitted by the transmitting base station after being reflected by the target. The echo signal is analyzed to include at least: time delay measurement and Doppler factor measurement.

3. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, The steps involved in constructing the impulse response model are as follows: Construct the initial impulse response model: ； In the formula, Describing the Dirac function, It is the total number of paths. and They are the first The time-varying amplitude and time-varying delay of each path; In a short period of time, assume the time-varying amplitude of the path If it is a constant, then the time-varying amplitude of the path For time-independent parameters Then time-varying delay Approximate expression: ； In the formula, yes The zeroth-order Taylor expansion; For the first The rate of change of path delay; The impulse response model is then: 。 4. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, When the received signal is obtained in step S2, the following steps are included: When the transmitted detection signal is At that time, the received signal without considering noise for: ； In the formula, For delay Differential calculations; definition and Then the received signal without considering noise Simplified to: ； In the formula, and They are the first Doppler factor and time delay for each path.

5. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, In step S3, the detection signal is a linear frequency modulated signal, then the received signal... include: ； In the formula, It is additive Gaussian noise; For a constant linear frequency modulated signal, t is the complex representation; t is time. ; For the number of paths, The path contains One unknown parameter, The set of unknown parameters yields a vector form of the unknown parameters: The elements in the vector form of the unknown parameters are represented as ;and: ； In the formula, ; ; and These are the amplitude, starting frequency, modulation slope, and initial phase of the linear frequency modulated signal, respectively. If the sampling frequency is Hz, resulting in a sampling period of Then the vector form of the unknown parameters The Fisher information matrix is ​​represented as: ； In the formula, For the matrix blocks of the Fisher information matrix: ； In the formula, and The value range is 1 to , The standard deviation of the noise; This is for the operation of taking the real part; The sampling sequence number; The number of samples; This is a conjugate operation; ； Based on the Fisher information matrix representation, the channel parameter estimation is obtained using Cramerro. for: 。 6. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, The parameters related to time delay and Doppler factor in step S4 are: ; Vector form of unknown parameters Fisher information matrix representation Block representation: ； In the formula, ; ; ; ; The parameters related to time delay and Doppler factor are obtained using the block matrix inversion theorem. Clamelo's Lower Realm : 。 7. The positioning method based on joint time delay and Doppler estimation according to claim 1, characterized in that, When the lower bound of Cramérault is obtained as described in step S5, the vector parameters are defined. Then the lower bound of the time delay and Doppler factor is Clamer-Rao. for: ； In the formula, .

8. A positioning system based on joint estimation of time delay and Doppler, characterized in that, The localization method based on joint time delay and Doppler estimation according to any one of claims 1-7 includes: The initialization unit is configured to: construct an impulse response model with a broadband underwater acoustic multipath channel based on a bistatic measurement system; The first processing unit is configured to: obtain the received signal based on the impulse response model and the detection signal; The second processing unit is configured to: use a linear frequency modulated signal for the detection signal, and obtain the Cramer-Rao lower bound of the channel parameter estimation based on the received signal; The third processing unit is configured to: obtain the lower bound of the parameters related to the time delay and the Doppler factor based on the lower bound of the channel parameter estimation; The output unit is configured to: obtain the lower bounds of the time delay and Doppler factor based on the Cramer-Rao lower bounds of the time delay and Doppler factor using the chain rule; use the lower bounds of the time delay and Doppler factor as the covariance matrix of the time delay and Doppler factor; and perform target localization based on the covariance matrix.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and, The memory is communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the localization method based on time delay and Doppler joint estimation as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the localization method based on joint time delay and Doppler estimation as described in any one of claims 1 to 7.

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