An Improved Fast Intelligent Tracking Algorithm with the Gain Adjustable

2012 ◽  
Vol 605-607 ◽  
pp. 1748-1752
Author(s):  
Dong Sen Si ◽  
Xiao Xu Wang ◽  
Chen Chen
Keyword(s):  
Adaptive Learning ◽  
Output Signal ◽  
Dynamic Change ◽  
Signal Strength ◽  
Tracking Algorithm ◽  
Dynamic Adjustment ◽  
Signal Gain ◽  
Linear Probe ◽  
Four Quadrant ◽  
Intelligent Tracking

Realize the goal quick and accurate location when the detection signal is weaker, puts forward a Fast Intelligent Tracking algorithm(FITA) with the Gain Adjustable. Wiht the goal image move in four quadrant detector, it’s size, location and output signal related to a linear probe interval. In this interval, a liner relation can be get between the spot position and the corresponding output signal. The target quick location algorithm is realized with this relation. On the other hand, the sum signal of the four quadrant detector is sampled in real-time, this sum is related to the sensor’s signal strength, then the change rate of the signal strength can be get, using adaptive learning ways to get the change trend of signal strength, and realized dynamic adjustment of the signal gain, in order to improve the signal resolution ratio when signal is weak, the tracking accuracy can be improved with this way. The experimental data show that FITA algorithm can rapidly locate position in the linear interval and accurately track through the dynamic change signal gain for the weaker signal. The track error can be improved to 1.9%.

Gain Adjustable Intelligent Tracking Algorithm

2012 ◽  
Vol 538-541 ◽  
pp. 2602-2606
Author(s):  
Dong Sen Si ◽  
Xiao Xu Wang ◽  
Chen Chen
Keyword(s):  
Adaptive Learning ◽  
Output Signal ◽  
Dynamic Change ◽  
Signal Strength ◽  
Dynamic Adjustment ◽  
Tracking Accuracy ◽  
Signal Gain ◽  
Linear Probe ◽  
Four Quadrant ◽  
Intelligent Tracking

Puts forward a Gain Adjustable Fast Intelligent Tracking (GAFIT) algorithm, and realize quick and accurate location of the goal, when the detection signal is weaker. According to the size, location and output signal of the goal in four quadrant detector, the linear probe interval is determined in the four quadrant detector. On this interval, a liner relation can be get between the spot position and the corresponding output signal. The target quick location is realized with this relation. On the other hand, the sum signal of the four quadrant detector is sampled in real-time, this sum is related to the sensor’s signal strength, then the change rate of the signal strength can be get, using adaptive learning ways to get the change trend of signal strength, and realized dynamic adjustment of the signal gain, in order to improve the signal resolution ratio when signal is weak, the tracking accuracy can be improved with this way. The experimental data show that GAIFT algorithm can rapidly locate position in the linear interval and accurately track through the dynamic change signal gain for the weaker signal. tracking precision can be improved to 0.018 degrees

NOVEL IMPLANT DEVICE TRACKING ALGORITHM FOR WIRELESS HEALTH MONITORING IN WBAN

2011 ◽  
Vol 25 (31) ◽  
pp. 4145-4148
Author(s):  
CHONG HYUN LEE ◽  
JINHO BAE ◽  
JOON-YOUNG KIM
Keyword(s):  
Body Movement ◽  
Wireless Body Area Network ◽  
Signal Strength ◽  
Tracking Algorithm ◽  
Position Tracking ◽  
Area Network ◽  
Human Tissues ◽  
Wireless Health ◽  
Body Area ◽  
Position Information

Positioning implant device in WBAN(Wireless Body Area Network) becomes difficult since signal strength varies in different human tissues and shadowing noise due to body movement. We propose a novel tracking algorithm in WBAN. To estimate position under various human tissues, we adopt a sliding linear window using past position information. By adjusting window parameters, the proposed algorithm is to reduce noise and to track position. The proposed algorithm has little computational increment as compared to the α-β tracker. Throughout simulations, we verify outstanding position tracking performance and insensitivity of initial parameters.

scholarly journals A New Intelligent Tracking Algorithm Using Fuzzy Kalman Filter

2005 ◽  
Vol 15 (5) ◽  
pp. 593-598 ◽  
Author(s):  
Sun-Young Noh ◽  
Young-Hoon Joo ◽  
Jin-Bae Park
Keyword(s):  
Kalman Filter ◽  
Tracking Algorithm ◽  
Intelligent Tracking

scholarly journals Advanced Vehicle Security and Location Sensing System by using a Single Wireless Device RSSI

2020 ◽  
Vol 9 (1) ◽  
pp. 1554-1559
Keyword(s):  
Dynamic Change ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Sensing System ◽  
Wireless Device ◽  
Vehicle Security ◽  
Received Signal Strength Indication ◽  
Location Sensing

Existing investigates on the spot pursue following spotlight either altogether on indoor or totally on outside by exploitation of various gadgets and strategies. This paper expects to follow a client position in each indoor and outside conditions by utilizing a solitary remote gadget with insignificant pursue blunder. RSSI (Received Signal Strength Indication) method alongside smoothing calculations is intended to cook this answer. The arranged RSSI-based pursue system is part into 2 principle stages, especially the normalization of RSSI coefficients and accordingly the separation together with position estimation of client area by reiterative trilateration. A low quality RSSI smoothing recipe is authorized to lessen the dynamic change of radio sign got from each reference hub once the objective hub is moving. Test estimations square measure distributed to examine the affectability of RSSI. The outcomes uncover the attainability of those calculations in concocting a great deal of right timeframe position watching framework.

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