Multiples are to be expected in this evolution, especially for something like PDR...

here is PNI talking

Home » Becky Oh presents webinar on 10/7 for MEMS Industry Group: Pedestrian Dead Reckoning Accuracy in Today's MEMS Sensors.

PEDESTRIAN DEAD RECKONING ACCURACY IN TODAY’S MEMS SENSORS

Please join us on October 7^th as PNI Sensor President  Becky Oh presents a webinar for the MEMS Industry Group discussing the pedestrian dead reckoning accuracy that can be achieved using today’s MEMS sensors in mobile phones.

According to ABI research, the Indoor Navigation market is forecasted to grow from $30 million in 2013 to 12.9 billion in 2018.  While there are many technologies being leveraged to provide indoor navigation, each has barriers that hinder wide scale adoption of a highly accurate solution. As such, there is a shift towards using multiple technologies together to provide a hybrid solution. The most promising of these is the combination of Wi-Fi, Bluetooth, Cellular and motion MEMS sensors, namely sensor fusion of gyroscopes, accelerometers and magnetic sensors. The accuracy one can achieve with today’s MEMS sensors found in mobile phones will be presented along with what effect this accuracy has on integration with other RF signals.

Date: Tuesday, October 7^th from 11:30 am – 12:30 pm EDT

For more details and to register, please reference the MEMS Industry Group events webpage:

http://www.memsindustrygroup.org/events/event_details.asp?id=475814&group=

This is true for QUIK, who is also working on a solution.  If you dummy Indoor location down, ie less sensors, less fusion it won't know where you are.  So it's 12 axis ( same as S2) is complex fusion.  It's what QUIK is hiring for also....as follows

JOB DESCRIPTION

The senior staff algorithm engineer plays a key role in developing advanced Pedestrian Dead Reckoning (PDR) algorithms on QuickLogic’s sensor hub for smartphone and wearable.  Strong algorithm development experience, with the ability to collaborate with multi-disciplined engineering teams, is required for success in this position.

Key result areas for this position are: 

• Develop, enhance and maintain advanced sensor algorithms focusing on Pedestrian Dead Reckoning (PDR) on QuickLogic’s smart-sensor CSSP products for mobile platforms 

• Key member of the team for full development cycle of sensor algorithm development: requirements and specifications, simulation, efficient implementation, system integration, optimization and testing 

• Responsible for developing data collection and testing methodology for sensor fusion and PDR algorithms. Provide guidance for the sensor data collection operation and sensor algorithm testing implementation 

• Support marketing, field, and engineering team in engagement with key customers to ensure successful integration, qualification and deployment of QuickLogic’s smart sensor into mobile platforms

Key Activities/Tasks for these positions are:

• Work closely with sensor hub architects and other team members for developing advanced Sensor fusion and PDR algorithms 

• The development activities include algorithm modeling and simulation, implementation using C and Assembly, performance tuning for various use cases, optimization for memory footprint and computation load 

• The development activities also include design and implementation of the testing method and apparatus for sensor fusion, inertial navigation and PDR algorithm. Design and implement the sensor data collection, visualization and annotation for sensor fusion and PDR algorithms and other algorithms. 

• The engineer will work closely with firmware, software and hardware team for system level design, implementation, integration, testing and deployment 

• In this role, the engineer will work with our partners, customers, and engineering teams for generating the technical requirements and generating the system and algorithm specifications for smart sensor CSSP products. 

• The engineer will support the teams and activities for key customer engagement to ensure key design wins and successful integration, qualification and deployment of the smart sensor CSSP products.

QUALIFICATIONS

• MS with 10+ years in electrical engineering or computer science is required. PhD with 7+ years in electrical engineering or computer science is preferred
• Expert level in algorithm development in the area of modern estimation theory, including Kalman filtering, automatic control and system theory, digital signal processing. Familiar with algorithm development tools such as Matlab and Simulink.
• Experience in efficient implementation of floating point and fixed point algorithms in firmware, software and hardware.
• Demonstrated ability to successfully complete complex R&D technology projects
• Must be able to work in team environment

     

The following experience is highly desired:

• Prior experience in the following related areas: indoor positioning systems (using inertial sensors, magnetometers, and pressure sensor, as well as information from wireless local area network, IR and RF transponders, and ultra-wideband (UWB) networks, 2D and 3D active and passive imaging sensors, and map database), simultaneous localization and map database (SLAM),  sensor fusion algorithm using motion sensors, user context and positioning system such as GNSSs, WiFi and BLE beacons, integrated personal navigation in the mixed indoor-outdoor environments, inertial navigation, and GPS
• System architecture experience

Complex stuff, if you get it right- things are different for you.    We have been at work on this for some time....time will tell who does it best.  APplication solutions are not ALL equal in importance.  PDR is HUGE for everyone...