Passive Sensor Network Clock Synchronization via Centralized Server
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Solution Overview
Problem
Existing sensor networks face challenges in synchronization and localization due to the need for costly and power-consuming clock synchronization methods, and are vulnerable to jamming and spoofing, especially in critical infrastructure systems like GNSS.
Innovation Solution
A method that uses unsynchronized sensors to synchronize clocks and perform localization and navigation by measuring signal times of arrival from multiple sources, including satellites and terrestrial sources, without requiring mutual synchronization, using iterative optimization processes and convex optimization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If very accurate clocks (such as atomic clocks) or GPS receivers are equipped with each sensor to maintain synchronization, then synchronization accuracy is improved, but system cost increases
Solution Approach 1:
The patent introduces a centralized server as an intermediary that performs the complex synchronization calculations. Instead of equipping each sensor with expensive atomic clocks or GPS receivers, the sensors simply record TOA measurements and transmit them to the server, which then computes the clock offsets and skews using iterative optimization processes. This mediator approach centralizes the computational complexity while keeping individual sensor units simple and inexpensive.
Solution Approach 2:
The patent replaces the physical hardware-based synchronization mechanisms (atomic clocks, GPS receivers) with a software-based computational approach. The synchronization is achieved through mathematical optimization algorithms that process TOA measurements, substituting the need for specialized hardware with algorithmic processing that can be performed on ordinary computers or servers.
2Measurement precision
If very accurate clocks (such as atomic clocks) or GPS receivers are equipped with each sensor to maintain synchronization, then synchronization accuracy is improved, but power consumption increases
Solution Approach 1:
The centralized server acts as an intermediary that handles the computationally intensive synchronization tasks. Individual sensors only need to perform simple TOA measurements and transmit data to the server, avoiding the need for power-intensive atomic clocks or GPS receivers at each sensor location. This distribution of computational load significantly reduces power consumption at the sensor level.
Solution Approach 2:
The patent substitutes power-consuming hardware-based timekeeping mechanisms with a low-power software-based approach. Sensors use ordinary clocks that consume minimal power, and the synchronization is achieved through data processing at a centralized server rather than through continuous operation of expensive, power-intensive hardware at each sensor node.
3Measurement precision
If two-way messaging or two-way TOA ranging is used between sensors to maintain synchronization, then synchronization is improved, but sensor cost and complexity increase
Solution Approach 1:
Instead of having sensors actively communicate with each other through two-way messaging or ranging, the patent inverts the approach: sensors passively receive signals from external sources and unilaterally transmit their TOA measurements to a centralized server. This eliminates the need for complex bidirectional communication protocols and sensors only need simple transmit capabilities.
Solution Approach 2:
The centralized server serves as an intermediary that collects TOA data from all sensors and performs the synchronization calculations. This eliminates the need for direct sensor-to-sensor communication, simplifying the sensor design while maintaining synchronization capability through the centralized coordination approach.
4Measurement precision
If two-way messaging or two-way TOA ranging is used between sensors to maintain synchronization, then synchronization is improved, but power consumption increases
Solution Approach 1:
The patent inverts the traditional active synchronization approach by having sensors passively record TOA measurements and unilaterally transmit data to a server. This eliminates the need for power-intensive two-way communication protocols, reducing overall system power consumption while maintaining synchronization capability through centralized processing.
5Measurement precision
If GNSS signals are used for time and positioning in critical infrastructures, then positioning accuracy is improved, but vulnerability to jamming increases
Solution Approach 1:
The patent converts the weakness of relying on external signals into a strength by using multiple independent signal sources (satellite signals and terrestrial signals from broadcast towers or cellular base stations). Instead of being vulnerable to jamming of a single GNSS constellation, the system can selectively use signals from multiple sources, and the iterative optimization process can identify and exclude jammed signals, turning the potential harm into a robust multi-source approach.
Solution Approach 2:
The patent changes the parameter of signal diversity by incorporating both satellite-based and terrestrial-based signal sources. This parameter change allows the system to operate in environments where GNSS may be jammed, as terrestrial signals provide an alternative source that is less susceptible to space-based jamming, thereby reducing overall vulnerability while maintaining positioning accuracy.
Data Source
AI summary
A method for sensor operation includes deploying a network of sensors (22), which have respective clocks (36) that are not mutually synchronized. At least a group of the sensors receive respective signals emitted from each of a plurality of sources (24, 26), and record respective times of arrival of the signals at the sensors according to the respective clocks. Location information is provided, including respective sensor locations of the sensors. The respective clocks are synchronized based on the recorded times of arrival and on the location information. In the process the sources may be localized, or if the sources are far away, then their directions may be resolved. Sensor positions may also be resolved in the process.


