WO2023221655A1 - Procédé d'estimation conjointe pour position cible et paramètre de propagation environnementale de réseau sous-marin de capteurs sans fil - Google Patents

Procédé d'estimation conjointe pour position cible et paramètre de propagation environnementale de réseau sous-marin de capteurs sans fil Download PDF

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WO2023221655A1
WO2023221655A1 PCT/CN2023/084119 CN2023084119W WO2023221655A1 WO 2023221655 A1 WO2023221655 A1 WO 2023221655A1 CN 2023084119 W CN2023084119 W CN 2023084119W WO 2023221655 A1 WO2023221655 A1 WO 2023221655A1
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Prior art keywords
node
anchor node
target
distance
signal
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PCT/CN2023/084119
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English (en)
Chinese (zh)
Inventor
梅骁峻
韩德志
吴中岱
王骏翔
郭磊
胡蓉
韩冰
徐一言
杨珉
朱宇
Original Assignee
上海船舶运输科学研究所有限公司
上海海事大学
中远海运科技股份有限公司
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Publication of WO2023221655A1 publication Critical patent/WO2023221655A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
    • H04B13/02—Transmission systems in which the medium consists of the earth or a large mass of water thereon, e.g. earth telegraphy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the invention relates to the technical field of underwater wireless sensor network node positioning, and specifically relates to a joint estimation method of target position and environmental propagation parameters.
  • UWSNs Underwater Wireless Sensor Networks
  • the purpose of this invention is to provide a joint estimation method (TLESE) for underwater sensor network target positions and environmental propagation parameters to solve the problem of reduced positioning accuracy caused by signal layering effects and unknown environmental parameters in highly dynamic marine environments. .
  • TLESE joint estimation method
  • a joint estimation method for underwater sensor network target position and environmental propagation parameters which is characterized by including the following steps:
  • a represents the gradient parameter
  • b represents the propagation speed of sound waves on the water surface
  • ⁇ i and ⁇ x represent the received signal angle of the i-th anchor node and the target node respectively, and their value range is [- ⁇ /2, ⁇ /2 ]; According to the distance of the target node Construct a ranging model of received signal strength;
  • N is the number of buoy sensor nodes deployed underwater that contain position information.
  • a ranging model of received signal strength based on Snell's law is constructed, specifically including:
  • N buoy sensor nodes containing position information are deployed underwater, that is, anchor nodes and a target node. Assume that the position of the i-th anchor node at time t is Target node at time t The location is Assume that all nodes are equipped with pressure sensors and can accurately know their own depth information; according to the propagation speed model of acoustic signals underwater, we can get:
  • a represents the gradient parameter
  • z represents the water depth
  • b represents the acoustic wave propagation speed on the water surface
  • C(z) represents the acoustic signal propagation velocity solution function when the water depth is z.
  • ⁇ i and ⁇ x represent the received signal angle of the i-th anchor node and the target node respectively, and their value range is [- ⁇ /2, ⁇ /2]; k represents a constant.
  • ⁇ f represents the absorption factor of the signal, which can be obtained according to the emission frequency according to Thorpe's theorem, that is:
  • the objective function with environmental propagation parameters and target position as variables is constructed through multiple first-order Taylor series expansions, specifically including:
  • d 0 is the reference distance, usually 1m, represents the power of the target node received by the i-th anchor node at time t, ⁇ t represents the environmental propagation parameter of the signal;
  • equation (7) in S22 can be expressed as:
  • ⁇ t represents the environmental propagation parameter of the signal
  • ⁇ t represents the environmental propagation parameter of the signal
  • ⁇ t represents the environmental propagation parameter of the signal
  • equation (10) in S25 is still nonlinear and difficult to solve, so it is assumed is smaller, using Taylor's first-order expansion of the exponential function, for Perform Taylor's first-order expansion, which can be further transformed into:
  • ⁇ t represents the environmental propagation parameter of the signal
  • I and 0 represent the identity matrix and zero matrix respectively.
  • the dichotomy method is used to conduct coarse-grained estimation of variables, specifically including:
  • the estimated value of the environmental propagation parameter is Among them, ⁇ t
  • the average value of the loss factor that is:
  • step S4 linear expansion is performed based on the coarse-grained estimated value and iterative re-optimization is performed to further improve the accuracy of the solution and obtain the estimated value of the target position, which specifically includes:
  • the present invention Compared with the existing technology, the present invention has the following advantages: it establishes a UWSNs ranging model with a layered effect and unknown environmental propagation parameters, and can jointly estimate the environmental propagation parameters and target position at each moment, thereby improving the accuracy of positioning.
  • this invention considers the propagation of underwater acoustic signals, the scene is 3D, and it also takes into account the layered effect of signal propagation underwater. And the ranging model constructed by absorption effect.
  • the solution method proposed by the present invention combines the dichotomy method and the linear re-optimization method based on Taylor series expansion, which is obviously different from the related methods in Chapter 5 of the paper. More importantly, the method proposed by the present invention is targeted at underwater scenes, and has significant improvements in computational complexity and accuracy. Therefore, the present invention is suitable for positioning field
  • the scene, model establishment and algorithm solution process are all essentially different from Chapter 5 of this paper, and the positioning performance of this invention is better than the method proposed in Chapter 5 of this paper.
  • Figure 1 is a flow chart of a joint estimation method of underwater sensor network target position and environmental propagation parameters according to the present invention.
  • Figure 2(a) and Figure 2(b) show the estimation errors corresponding to different numbers of anchor nodes in the present invention.
  • Figure 3(a) and Figure 3(b) show the estimation errors of the target position and environmental propagation parameters (path loss factor) of different anchor nodes in the present invention.
  • Figure 4(a) and Figure 4(b) show the estimation errors corresponding to the target position and environmental propagation parameters (path loss factor) of different absorption factors according to the present invention.
  • Figure 1 shows a flow chart of a joint estimation method of underwater sensor network target position and environmental propagation parameters of the present invention, which specifically includes:
  • a represents the gradient parameter
  • b represents the propagation speed of sound waves on the water surface
  • ⁇ i and ⁇ x represent the received signal angle of the i-th anchor node and the target node respectively, and their value range is [- ⁇ /2, ⁇ /2 ]; According to the distance of the target node Construct a ranging model of received signal strength;
  • N is the number of buoy sensor nodes deployed underwater that contain position information.
  • step S1 specifically includes:
  • N buoy sensor nodes containing position information are deployed underwater, that is, anchor nodes and a target node.
  • the position of the i-th anchor node at time t is The position of the target node at time t is Assume that all nodes are equipped with pressure sensors and can accurately know their own depth information; according to the propagation speed model of acoustic signals underwater, we can get:
  • a represents the gradient parameter
  • z represents the water depth
  • b represents the acoustic wave propagation speed on the water surface
  • C(z) represents the acoustic signal propagation velocity solution function when the water depth is z.
  • ⁇ i and ⁇ x represent the received signal angle of the i-th anchor node and the target node respectively, and their value range is [- ⁇ /2, ⁇ /2]; k represents a constant.
  • ⁇ f represents the absorption factor of the signal, which can be obtained according to the emission frequency according to Thorpe's theorem, that is:
  • the step S2 specifically includes:
  • d 0 is the reference distance, usually 1m, represents the power of the target node received by the i-th anchor node at time t, and ⁇ t represents the environmental propagation parameter of the signal.
  • equation (7) in S22 can be expressed as:
  • ⁇ t represents the environmental propagation parameter of the signal.
  • equation (10) in S25 is still nonlinear and difficult to solve, so it is assumed is smaller, using Taylor's first-order expansion of the exponential function, for Perform Taylor's first-order expansion, which can be further transformed into:
  • ⁇ t represents the environmental propagation parameter of the signal
  • I and 0 represent the identity matrix and zero matrix respectively.
  • the step S3 specifically includes:
  • the estimated value of the environmental propagation parameter is Among them, ⁇ t
  • the average value of the loss factor that is:
  • the step S4 specifically includes:
  • TLESE algorithm In order to verify the effectiveness of the method of the present invention (referred to as TLESE algorithm), simulation experiments were conducted in Matlab R2021b. For different scenarios, compare the existing algorithms USR, PLSE, and TSE, and use the minimum root mean square error (RSME) as the evaluation index to evaluate the performance of the algorithm, namely:
  • MC represents the total number of Monte Carlo simulations; nu represents the number of Monte Carlo simulations.
  • the anchor node and target node positions of each Monte Carlo simulation are set to change in the simulation.
  • the method TLESE proposed by the present invention incorporates the linear iterative re-optimization method, and its positioning accuracy is significantly better than the other three methods. The same result can be obtained from the environmental parameter estimation error in Figure 2(b). Although the environmental parameter estimation error of the method proposed in this invention increases as the noise increases, the overall estimation performance is better than the other three methods.
  • the received signal strength (RSS) information that can be used to estimate underwater acoustic signal propagation also increases, so the estimation error of each algorithm decreases as the number of anchor nodes increases.
  • the advantages of TLESE's positioning performance gradually become apparent, and its position estimation accuracy is better than the other three methods. This superiority is further illustrated in the environmental propagation parameter estimation error in Figure 3(b).

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

La présente invention concerne un procédé d'estimation conjointe pour une position cible et un paramètre de propagation environnementale d'un réseau sous-marin de capteurs sans fil. Le procédé comprend les étapes suivantes : S1, selon un effet de propagation en couches d'un signal sonore sous l'eau, construire un modèle de télémétrie d'une intensité de signal reçu selon la loi de Snell et un théorème de lancer de rayons ; S2, au moyen d'une pluralité d'expansions de série de Taylor de premier ordre, construire une fonction objectif en utilisant comme variables un paramètre de propagation environnementale et une position cible ; S3, effectuer une estimation grossière des variables par dichotomie ; et S4, effectuer une expansion linéaire selon la valeur de l'estimation grossière, et effectuer une réoptimisation itérative pour améliorer davantage la précision d'une solution. Le procédé présente les avantages de résoudre le problème d'une erreur de positionnement accrue résultant d'un paramètre de propagation environnementale inconnu et d'un effet de couches dans un processus de propagation de signal sous-marin.
PCT/CN2023/084119 2022-05-17 2023-03-27 Procédé d'estimation conjointe pour position cible et paramètre de propagation environnementale de réseau sous-marin de capteurs sans fil WO2023221655A1 (fr)

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CN202210536969.5A CN115038165B (zh) 2022-05-17 2022-05-17 一种水下无线传感网目标位置和环境传播参数的联合估计方法

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CN115038165B (zh) * 2022-05-17 2023-05-12 上海船舶运输科学研究所有限公司 一种水下无线传感网目标位置和环境传播参数的联合估计方法
CN116299393A (zh) * 2023-02-24 2023-06-23 烟台欣飞智能系统有限公司 基于多目标检测的隐身雷达高精度导航定位系统

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