Sensor fusion is the combining of sensor

Sensor

A sensor is a device that measures a physical quantity and converts it into a signal which can be read by an observer or by an instrument. For example, a mercury-in-glass thermometer converts the measured temperature into expansion and contraction of a liquid which can be read on a calibrated...

y data or data derived from sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The term better in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic

Stereoscopy

Stereoscopy refers to a technique for creating or enhancing the illusion of depth in an image by presenting two offset images separately to the left and right eye of the viewer. Both of these 2-D offset images are then combined in the brain to give the perception of 3-D depth...

 vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints).

The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish direct fusion, indirect fusion and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensor

Soft sensor

Soft sensor or virtual sensor is a common name for software where several measurements are processed together. There may be dozens or even hundreds of measurements. The interaction of the signals can be used for calculating new quantities that need not be measured...

s, and history values of sensor data, while indirect fusion uses information sources like a priori

A priori and a posteriori (philosophy)

The terms a priori and a posteriori are used in philosophy to distinguish two types of knowledge, justifications or arguments...

 knowledge about the environment and human input.

Sensor fusion is also known as (multi-sensor) Data fusion

Data fusion

Data fusion, is generally defined as the use of techniques that combine data from multiple sources and gather that information into discrete, actionable items in order to achieve inferences, which will be more efficient and narrowly tailored than if they were achieved by means of disparate...

and is a subset of information fusion.

Examples of sensors

• Radar
  Radar
  Radar is an object-detection system which uses radio waves to determine the range, altitude, direction, or speed of objects. It can be used to detect aircraft, ships, spacecraft, guided missiles, motor vehicles, weather formations, and terrain. The radar dish or antenna transmits pulses of radio...
  
  
• Sonar
  Sonar
  Sonar is a technique that uses sound propagation to navigate, communicate with or detect other vessels...
  
   and other acoustic
• Infra-red / thermal imaging camera
• TV cameras
• Sonobuoy
  Sonobuoy
  A sonobuoy is a relatively small expendable sonar system that is dropped/ejected from aircraft or ships conducting anti-submarine warfare or underwater acoustic research....
  
  s
• Seismic sensor
  Seismometer
  Seismometers are instruments that measure motions of the ground, including those of seismic waves generated by earthquakes, volcanic eruptions, and other seismic sources...
  
  s
• Magnetic sensor
  Magnetometer
  A magnetometer is a measuring instrument used to measure the strength or direction of a magnetic field either produced in the laboratory or existing in nature...
  
  s
• Electronic Support Measures (ESM)
• Phased array
  Phased array
  In wave theory, a phased array is an array of antennas in which the relative phases of the respective signals feeding the antennas are varied in such a way that the effective radiation pattern of the array is reinforced in a desired direction and suppressed in undesired directions.An antenna array...
  
  
• MEMS
• Accelerometer
  Accelerometer
  An accelerometer is a device that measures proper acceleration, also called the four-acceleration. This is not necessarily the same as the coordinate acceleration , but is rather the type of acceleration associated with the phenomenon of weight experienced by a test mass that resides in the frame...
  
  s

Sensor fusion algorithms

Sensor fusion is a term that covers a number of methods and algorithms, including:

• Kalman filter
  Kalman filter
  In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise and other inaccuracies, and produce values that tend to be closer to the true values of the measurements and their associated calculated...
  
  
• Bayesian network
  Bayesian network
  A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph . For example, a Bayesian network could represent the probabilistic...
  
  s
• Dempster-Shafer

Centralized versus decentralized

In sensor fusion, centralized versus decentralized refers to where the fusion of the data occurs. In centralized fusion, the clients simply forward all of the data to a central location, and some entity at the central location is responsible for correlating and fusing the data. In decentralized, the clients take full responsibility for fusing the data. "In this case, every sensor or platform can be viewed as an intelligent asset having some degree of autonomy in decision-making."

Multiple combinations of centralized and decentralized systems exist.

Levels

There are several categories or levels of sensor fusion that are commonly used.

• Level 0 – Data alignment
• Level 1 – Entity assessment (e.g. signal/feature/object)
  • Tracking and object detection/recognition/identification
• Level 2 – Situation assessment
• Level 3 – Impact assessment
• Level 4 – Process refinement (i.e. sensor management)
• Level 5 – User refinement

See also

• Information integration
  Information integration
  Information integration is the merging of information from disparate sources with differing conceptual, contextual and typographical representations. It is used in data mining and consolidation of data from unstructured or semi-structured resources...
  
  
• Data mining
  Data mining
  Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...
  
  
• Data fusion
  Data fusion
  Data fusion, is generally defined as the use of techniques that combine data from multiple sources and gather that information into discrete, actionable items in order to achieve inferences, which will be more efficient and narrowly tailored than if they were achieved by means of disparate...
  
  
• Image fusion
  Image fusion
  In computer vision, Multisensor Image fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images....
  
  
• Information: Information is not data
• Data (computing)
  Data (computing)
  In computer science, data is information in a form suitable for use with a computer. Data is often distinguished from programs. A program is a sequence of instructions that detail a task for the computer to perform...
  
  
• multimodal integration
  Multimodal integration
  Multimodal integration, also known as multisensory integration, is the study of how information from the different sensory modalities, such as sight, sound, touch, smell, self-motion and taste, may be integrated by the nervous system. A coherent representation of objects combining modalities...
  
  
• Fisher's method
  Fisher's Method
  In statistics, Fisher's method, also known as Fisher's combined probability test, is a technique for data fusion or "meta-analysis" . It was developed by and named for Ronald Fisher...
  
   for combining independent tests of significance
• Transducer Markup Language (TML) is an XML based markup language which enables sensor fusion.
• Brooks–Iyengar algorithm
  Brooks–Iyengar algorithm
  The Brooks–Iyengar algorithm or Brooks–Iyengar hybrid algorithm is a distributed algorithm, that improves both the precision and accuracy of the measurements taken by a distributed sensor network, even in the presence of faulty sensors. The sensor network does this by exchanging the measured...
  
  
• Inertial navigation system
  Inertial navigation system
  An inertial navigation system is a navigation aid that uses a computer, motion sensors and rotation sensors to continuously calculate via dead reckoning the position, orientation, and velocity of a moving object without the need for external references...