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RF Triangulator: Indoor/Outdoor Location Finding 18-525 Architecture Proposal Giovanni Fonseca David Fu Amir Ghiti Stephen Roos Design Manager: Myron Kwai.

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Presentation on theme: "RF Triangulator: Indoor/Outdoor Location Finding 18-525 Architecture Proposal Giovanni Fonseca David Fu Amir Ghiti Stephen Roos Design Manager: Myron Kwai."— Presentation transcript:

1 RF Triangulator: Indoor/Outdoor Location Finding 18-525 Architecture Proposal Giovanni Fonseca David Fu Amir Ghiti Stephen Roos Design Manager: Myron Kwai Overall Project Objective: Design a Radio-Frequency indoor/outdoor navigation system, utilizing the existing wireless infrastructure. Design Stage Objective: Implement functional (behavioral) Verilog description

2 New Design Proposal ► Using existing 802.11 wireless signals it is possible to calculate one’s location without the use of GPS. ► The RF Triangulator will use current infrastructures to act as an indoor/outdoor local positioning system ► By acquiring signal data from 3 or more wireless access points it will be possible to determine one’s coordinates to within 1 meter.

3 Triangulation Process ► Our chip will solve for the simultaneous solution of 3 circle equations.

4 RF Triangulator Applications: ► Our chip can be integrated into handheld computers, watches, or shopping carts for locations ranging from large theme parks to office buildings. ► It will be able to quickly provide your current location as well as provide a distance and heading to a future location for path-finding purposes.

5 Current Project Status: ► Finish debugging the behavioral description of the RF Triangulator chip ► Starting preparations for structural Verilog ► Deciding how many arithmetic units we need and comparing performance vs. size ► Optimizing main algorithms ► Deciding on timing/pipelining implementation

6 Design Decisions: ► We conceived a completely new and better design than the RF-ID credit card. ► We decided that the RF-ID credit card was mostly encryption based and lacked originality ► The 16-bit floating point precision is sufficiently precise for our application.

7 Design Decisions: ► Memory and caching is implemented to keep the 3 strongest signals readily available for position calculation. ► An SRAM lookup table stores individual access point data including: MAC address, X and Y coordinated, originating signal/noise ratio. ► A queue stores 4 more recently acquired signals, and allows for migration between the top 3 signals and the queue.

8 Functionality: ► It has the ability to write new map data into the ~1K SRAM lookup table ► After acquiring at least 3 signals it will output your current X and Y coordinates ► Has the ability to calculate the distance and heading (angle) to a given location.

9 Major Functional Components: ► Top 3 / Queue module Gives priority to the top 3 signals based on their Signal-to-Noise Ratios ► Lookup Table Module Hard coded data of MAC addresses, x and y coordinates as well as Signal-to-Noise Ratios (SNR). ► Calc Module Given the coordinates of 3 Access Points and their distance, it will calculate the current position. Given the coordinates of 3 Access Points and their distance, it will calculate the current position.

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12 Major Functional Components: ► Floating-point unit (FPU)  Performs the addition, subtraction, multiplication and division of floating-point numbers. ► Waypoint Calculator  Calculates distance and angle to requested destination  Relies on a trig lookup table

13 Underlying Assumptions: ► Map data will be available for the current location. ► An RF antenna with A/D converter will provide a signal with data from wireless access points. ► Access points will broadcast their MAC address. ► The user will not be moving quickly and/or moving out of map range.

14 Underlying Assumptions: ► The available signal quality will allow for good distance approximation. ► The power and location of the sending signal is included in the map data. ► No more than 16 bits of floating point precision are necessary for our calculations.

15 Calc Module: Triangulation Formula assign sqrt = q; assign Xr1 = (-b+sqrt)/(2*a); assign Xr1 = (-b+sqrt)/(2*a); assign Xr2 = (-b-sqrt)/(2*a); assign Xr2 = (-b-sqrt)/(2*a); assign Yr1 = A - B*Xr1; assign Yr1 = A - B*Xr1; assign Yr2 = A - B*Xr2; assign Yr2 = A - B*Xr2; assign result1 = (Xr1-rxC)*(Xr1-rxC)+(Yr1-ryC)*(Yr1- ryC)-dC; assign result1 = (Xr1-rxC)*(Xr1-rxC)+(Yr1-ryC)*(Yr1- ryC)-dC; assign result2 = (Xr2-rxC)*(Xr2-rxC)+(Yr2-ryC)*(Yr2- ryC)-dC; assign result2 = (Xr2-rxC)*(Xr2-rxC)+(Yr2-ryC)*(Yr2- ryC)-dC; if(result1 < 0) assign result1 = -result1; if(result1 < 0) assign result1 = -result1; if(result2 < 0) assign result2 = -result2; if(result2 < 0) assign result2 = -result2; if(result1 < result2) if(result1 < result2) begin begin assign xPos = $realtobits(Xr1); assign yPos = $realtobits(Yr1); end end else begin else begin assign xPos = $realtobits(Xr2); assign xPos = $realtobits(Xr2); assign yPos = $realtobits(Yr2); assign yPos = $realtobits(Yr2); end end assign dA = rsnoA/rsniA; assign dA = rsnoA/rsniA; assign dB = rsnoB/rsniB; assign dB = rsnoB/rsniB; assign dC = rsnoC/rsniC; assign dC = rsnoC/rsniC; assign A = (dA-dB+rxB*rxB- rxA*rxA)/(2*(ryB-ryA))+(ryB+ryA)/2; assign A = (dA-dB+rxB*rxB- rxA*rxA)/(2*(ryB-ryA))+(ryB+ryA)/2; assign B = (rxB-rxA)/(ryB-ryA); assign B = (rxB-rxA)/(ryB-ryA); assign a = a+B*B; assign a = a+B*B; assign b = 2*(ryA*B-rxA-A*B); assign b = 2*(ryA*B-rxA-A*B); assign c = rxA*rxA+ryA*ryA+A*A- 2*ryA*A-dA; assign c = rxA*rxA+ryA*ryA+A*A- 2*ryA*A-dA; assign delta = b*b-4*a*c; assign delta = b*b-4*a*c; //square root function //square root function q = 0; q = 0; y = 2; y = 2; for(i=0;i<14;i=i+1) for(i=0;i<14;i=i+1) begin begin q = delta/y; q = delta/y; y = (y+q)/2; y = (y+q)/2; end end

16 Questions/Concerns ► Transistor Count – Highly dependant on how many transistors we need for floating point calculations ► Speed – Will take >50 cycles to achieve a position calculation.


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