A Time-Based Angle-of-Arrival Sensor Using CMOS IR-UWB Transceivers

Yu, Byung Gyu; Lee, Geunhaeng; Han, Hong; Sang, Won; Kim, Tae Wook

doi:10.1109/jsen.2016.2567441

Cited by 15 publications

(6 citation statements)

References 40 publications

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“…From Equation (8), it is clear that a band-pass function round ω 0 , H bp (ω), determines the frequency response of the SR receiver to the RF input signal. This band-pass function is directly related to the conductance curve, G(t), during the time interval from t a1 to t b1 , according to Equation (4). Assuming a square-law model for the MOS transistors in Figure 2, G(t) in this time interval can approximately be expressed as…”

Section: Proposed Quench Generatormentioning

confidence: 99%

“…Impulse radio is a particular form of signaling in which short-duration pulses are transmitted, thereby spreading the energy of the radio signal over a relatively wide bandwidth [1][2][3][4]. Super-regenerative (SR) receiver architecture, invented in 1922 by Armstrong [5], is a promising front-end solution for low-power and low-cost impulse radio communications.…”

Section: Introductionmentioning

confidence: 99%

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Selectivity and sensitivity enhancement methods for high‐data‐rate super‐regenerative receiver

Mousavi

Saeedi

2017

Circuit Theory & Apps

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This paper describes selectivity and sensitivity performance evaluations and improvement methods for an on-off keying super-regenerative (SR) receiver. A slope-controlled quasi-exponential quench waveform, generated by a low-complexity PVT-tolerant quench generator circuit, is proposed to increase data rate and reduce the receiver 3-dB bandwidth, thereby preventing oscillation caused by out-of-band injected signals and improving the receiver selectivity. The SR receiver sensitivity is also enhanced by a noise-canceling front-end topology with single-ended to differential (S2D) signal converter. To exemplify these techniques, we designed an SR receiver with the proposed front-end and quench waveform generator in a 0.18-μm CMOS technology. Theoretical analyses and circuit simulations show 30% and 65% reduction in 3-dB bandwidth of the SR receiver at 25 Mbps data rate by employing the proposed quench signal compared with piecewise-linear and trapezoidal quench waveforms, respectively. Performance of the proposed front-end is evaluated by a fast bit-error-rate estimation procedure, based on circuit noise simulations and statistical analyses, without the need for time-consuming transient-noise simulations. Accuracy of the procedure has been verified by comparing its results with transient-noise simulations. According to the estimated bit-error-rate curves, the noise-canceling topology with S2D converter enhances the SR receiver sensitivity by 9 dB.The noise-canceling RF front-end with S2D conversion is shown in Figure 7. A common gate (CG)common source (CS) LNA topology is employed to provide input impedance matching and S2D conversion. Trans-conductance of the CG transistor, M 3 , is set to 20 mS for 50-Ω input impedance matching. The biasing circuit in Figure 2 is also employed in the LNA to reduce the effect of PVT variations on trans-conductance of M 3 and M 4 . Phase difference between the two signals injected by the CS transistor, M 4 , and the CG transistor, M 3 , to the SR oscillator core is about 180 degrees. The Figure 6. (a) The conductance curve, G(t); (b) the sensitivity pulse, s(t), and the normalized oscillation envelope, p(t); and (c) the super-regenerative band-pass function, |H bp (ω)|, of the proposed quench technique for three different values of G À and gain. Data rate is 25 Mbps in all cases.Figure 8. The super-regenerative oscillator output employing (a) the proposed S2D converter and (b) a single-ended LNA. (c) Histogram of the oscillator output low level, derived from Monte Carlo simulations.Figure 14. Transient-noise simulation of the super-regenerative receiver at 25 Mbps data rate: (a) the input pulse, (b) oscillator differential output, (c) envelope detector output, and (d) output signals of the comparator and the flip-flop.

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Section: Proposed Quench Generatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Selectivity and sensitivity enhancement methods for high‐data‐rate super‐regenerative receiver

Mousavi

Saeedi

2017

Circuit Theory & Apps

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“…The positioning principle is divided into two steps: (1) ranging which is measuring the distance between two points; (2) positioning which determines the location of the mobile tag according to the results of the ranging by a specific algorithm. There are four classic positioning methods which include received signal strength [3] (RSS), signal angle of arrival [4] (AOA), time of arrival [5] (TOA) and time difference of arrival [6] (TDOA). The TOA/TDOA scheme is the main ranging scheme for UWB positioning.…”

Section: Introductionmentioning

confidence: 99%

“…) and anchor4 ( 4 x ,4 y ) are the coordinates of the base stations, tag ( 5x , 5 y ) is the coordinate of the mobile tag, as shown inFigure.…”

mentioning

confidence: 99%

High-accuracy Positioning Algorithm Based on UWB

Yaqiu¹

2018

2018 3rd International Conference on Computer Science and Information Engineering (ICCSIE 2018)

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In the indoor positioning, it proposes a line to approximate hyperbola positioning algorithm based on ultra-wideband (UWB) aiming at the problems of low-accuracy positioning, non-line-of-sight (NLOS) phenomenon and multipath propagation in the precise positioning of mobile tags. The paper a method of using some lines to approximate hyperbola. It can convert quadratic hyperbolic equation into linear equation. Then it can achieve the high-accuracy position combining the time difference of arrival (TDOA) and triangle centroid position algorithm. According to MATLAB simulation, the average distance error of the three-line approximate algorithm is 23.7cm, the average distance error of the three-and-four-line approximate positioning algorithm is 17.7cm, and the average distance error of the five-line approximate positioning algorithm is 12.9cm. In the case of ensuring positioning accuracy, the Chan algorithm runs for a period of 14.5s. The maximum time is 7.9s for the algorithm to run one cycle, and the complexity of the algorithm is greatly reduced.

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“…Wireless positioning methods can be divided into fingerprint positioning algorithm based on received signal strength indicator (RSSI) [13], geometric or range positioning algorithm based on the range, time of arrival (TOA) [14,15], time difference of arrival (TDOA) [16], or angle of arrival (AOA) [17], and some fusion positioning methods together with inertial measurement units (IMUs) [5]. The signal fingerprint positioning algorithm [4,18] is based on the mapping relationship between some parameters obtained from the received signal and the position information of the target node.…”

Section: Introductionmentioning

confidence: 99%

Threshold selection method for UWB TOA estimation based on wavelet decomposition and kurtosis analysis

Cui

Song

et al. 2017

J Wireless Com Network

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In wireless sensor networks, ranging or positioning via ultra-wideband (UWB) has caused widespread research interests where the non-coherent energy detection (ED) method with low sampling rate and low complexity is widely studied. However, the traditional energy detection methods only analyze the signal energy in the time domain, so their error is relatively large. In this paper, the simulation results show that most of the signal energy concentrates in the low-frequency band, so a novel threshold selection method for time of arrival (TOA) estimation is proposed that analyzes the signals in both time domain and frequency domain. In this method, the received signal is decomposed by "db6" wavelet and the kurtosis of energy blocks of the low-frequency wavelet coefficients (K c ) is analyzed. At last, the mapping relationship between K c and the normalized threshold for TOA estimation is created using polynomial fitting with degree 3. The simulation results show that the TOA estimation error of the proposed method is significantly less than the method without wavelet decomposition.

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A Time-Based Angle-of-Arrival Sensor Using CMOS IR-UWB Transceivers

Cited by 15 publications

References 40 publications

Selectivity and sensitivity enhancement methods for high‐data‐rate super‐regenerative receiver

Selectivity and sensitivity enhancement methods for high‐data‐rate super‐regenerative receiver

High-accuracy Positioning Algorithm Based on UWB

Threshold selection method for UWB TOA estimation based on wavelet decomposition and kurtosis analysis

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