scholarly journals Frequency Estimation from Compressed Measurements of a Sinusoid in Moving-Average Colored Noise

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1852
Author(s):  
Nuha A. S. Alwan ◽  
Zahir M. Hussain
Keyword(s):  
Colored Noise ◽  
Frequency Estimation ◽  
Moving Average ◽  
Research Community ◽  
Wireless Sensor ◽  
Estimation Accuracy ◽  
Second Order Statistics ◽  
Acceptable Accuracy ◽  
Resource Limited ◽  
Recent Emergence

Frequency estimation of a single sinusoid in colored noise has received a considerable amount of attention in the research community. Taking into account the recent emergence and advances in compressive covariance sensing (CCS), the aim of this work is to combine the two disciplines by studying the effects of compressed measurements of a single sinusoid in moving-average colored noise on its frequency estimation accuracy. CCS techniques can recover the second-order statistics of the original uncompressed signal from the compressed measurements, thereby enabling correlation-based frequency estimation of single tones in colored noise using higher order lags. Acceptable accuracy is achieved for moderate compression ratios and for a sufficiently large number of available compressed signal samples. It is expected that the proposed method would be advantageous in applications involving resource-limited systems such as wireless sensor networks.

scholarly journals Frequency Estimation from Compressed Measurements of a Sinusoid in MA Colored Noise

2021 ◽  
Author(s):  
Nuha A. S. Alwan ◽  
Zahir M. Hussain
Keyword(s):  
Colored Noise ◽  
Frequency Estimation ◽  
Moving Average ◽  
Research Community ◽  
Wireless Sensor ◽  
Estimation Accuracy ◽  
Second Order Statistics ◽  
Acceptable Accuracy ◽  
Resource Limited ◽  
Recent Emergence

Frequency estimation of a single sinusoid in colored noise has received a considerable amount of attention in the research community. Taking into account the recent emergence and advances in compressive covariance sensing (CCS), the aim of this work is to combine the two disciplines by studying the effects of compressed measurements of a single sinusoid in moving-average (MA) colored noise on its frequency estimation accuracy. CCS techniques can recover the second-order statistics of the original uncompressed signal from the compressed measurements, thereby enabling correlation-based frequency estimation of single tones in colored noise using higher-order lags. Acceptable accuracy is achieved for moderate compression ratios and for a sufficiently large number of available compressed signal samples. It is expected that the proposed method would be advantageous in applications involving resource-limited systems such as wireless sensor networks.

FFT-Based Moving Average Maximum Likelihood Single-tone Frequency Estimation

2011 ◽  
Vol 30 (4) ◽  
pp. 831-835
Author(s):  
Yu-chun Huang ◽  
Zai-lu Huang ◽  
Ben-xiong Huang ◽  
Shu-hua Xu
Keyword(s):  
Maximum Likelihood ◽  
Frequency Estimation ◽  
Moving Average ◽  
Tone Frequency ◽  
Single Tone ◽  
Average Maximum

scholarly journals Phase Clustering Based Modulation Classification Algorithm for PSK Signal over Wireless Environment

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Qi An ◽  
Zi-shu He ◽  
Hui-yong Li ◽  
Yong-hua Li
Keyword(s):  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Frequency Offset ◽  
Estimation Accuracy ◽  
Modulation Classification ◽  
Electronic Warfare ◽  
Wireless Communication Network ◽  
Shift Keying ◽  
Analytical Formulas ◽  
Fractional Function

Promptitude and accuracy of signals’ non-data-aided (NDA) identification is one of the key technology demands in noncooperative wireless communication network, especially in information monitoring and other electronic warfare. Based on this background, this paper proposes a new signal classifier for phase shift keying (PSK) signals. The periodicity of signal’s phase is utilized as the assorted character, with which a fractional function is constituted for phase clustering. Classification and the modulation order of intercepted signals can be achieved through its Fast Fourier Transform (FFT) of the phase clustering function. Frequency offset is also considered for practical conditions. The accuracy of frequency offset estimation has a direct impact on its correction. Thus, a feasible solution is supplied. In this paper, an advanced estimator is proposed for estimating the frequency offset and balancing estimation accuracy and range under low signal-to-noise ratio (SNR) conditions. The influence on estimation range brought by the maximum correlation interval is removed through the differential operation of the autocorrelation of the normalized baseband signal raised to the power ofQ. Then, a weighted summation is adopted for an effective frequency estimation. Details of equations and relevant simulations are subsequently presented. The estimator proposed can reach an estimation accuracy of10-4even when the SNR is as low as-15 dB. Analytical formulas are expressed, and the corresponding simulations illustrate that the classifier proposed is more efficient than its counterparts even at low SNRs.

Security and Attacks in Wireless Sensor Networks

2011 ◽  
pp. 183-216 ◽  
Author(s):  
Murat Al ◽  
Kenji Yoshigoe
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Security ◽  
Communication Protocol ◽  
Research Community ◽  
Wireless Sensor ◽  
General View ◽  
Wireless Technologies ◽  
Close Relationship

Understanding data security is crucial to the daily operation of Wireless Sensor Networks (WSNs) as well as to the further advancement of security solutions in the research community. Unlike many surveys in literature that handle the topic in close relationship to a particular communication protocol, we provide a general view of vulnerabilities, attacks, and countermeasures in WSNs, enabling a broader audience to benefit from the presented material. We compare salient characteristics and applications of common wireless technologies to those of WSNs. As the main focus of the chapter, we thoroughly describe the characteristics of attacks and their countermeasures in WSNs. In addition, we qualitatively illustrate the multi-dimensional relationship among various properties including the effectiveness of these attacks (i.e., caused damage), the resources needed by adversaries to accomplish their intended attacks (i.e., consumed energy and time), and the resources required to defend against these attacks (i.e., energy overhead).

scholarly journals Extraction and Filter Algorithm of Roll Angular Rate for High Spinning Projectiles

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Hui Zhao ◽  
Zhong Su ◽  
Fuchao Liu ◽  
Chao Li ◽  
Qing Li ◽  
...  
Keyword(s):  
Measurement Problem ◽  
Frequency Estimation ◽  
Angular Rate ◽  
Estimation Accuracy ◽  
Signal Frequency ◽  
Average Error ◽  
Accurate Estimation ◽  
Test Results ◽  
Narrowband Signal ◽  
Spinning Projectile

The accurate measurement of roll angular rate for high spinning projectile has long been a challenging problem. Aiming to obtain the accurate roll angular rate of high spinning projectile, a novel extraction and filter algorithm, BSCZT-KF, is proposed in this paper. Firstly, a compound angular motion model of high spinning projectile is established. According to the model, we translate the roll angular rate measurement problem into a frequency estimation problem. Then the improved CZT algorithm, BSCZT, was employed to realize an accurate estimation of the narrowband signal frequency. Combined with the peak detection method, the BSCZT-KF algorithm is presented to further enhance the frequency estimation accuracy and the real-time performance. Finally, two sets of actual flight tests were conducted to verify the effectiveness and accuracy of the algorithm. The test results show that the average error of estimated roll angular rate is about 0.095% of the maximum of roll angular rate. Compared with the existing methods, the BSCZT-KF has the highest frequency estimation accuracy for narrowband signal.

scholarly journals Accurate Frequency Estimation Based On Three-Parameter Sine-Fitting With Three FFT Samples

2015 ◽  
Vol 22 (3) ◽  
pp. 403-416 ◽  
Author(s):  
Xin Liu ◽  
Yongfeng Ren ◽  
Chengqun Chu ◽  
Wei Fang
Keyword(s):  
Fourier Transform ◽  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Golden Section ◽  
Least Square ◽  
Estimation Accuracy ◽  
Tone Frequency ◽  
Single Tone ◽  
Dc Component ◽  
Fitting Error

Abstract This paper presents a simple DFT-based golden section searching algorithm (DGSSA) for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT) and Discrete Fourier Transform (DFT) are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accuracy under conditions of a low signal-to-noise ratio (SNR) and a low resolution. This method firstly uses three FFT samples to determine the frequency searching scope, then – besides the frequency – the estimated values of amplitude, phase and dc component are obtained by minimizing the least square (LS) fitting error of three-parameter sine fitting. By setting reasonable stop conditions or the number of iterations, the accurate frequency estimation can be realized. The accuracy of this method, when applied to observed single-tone sinusoid samples corrupted by white Gaussian noise, is investigated by different methods with respect to the unbiased Cramer-Rao Low Bound (CRLB). The simulation results show that the root mean square error (RMSE) of the frequency estimation curve is consistent with the tendency of CRLB as SNR increases, even in the case of a small number of samples. The average RMSE of the frequency estimation is less than 1.5 times the CRLB with SNR = 20 dB and N = 512.

Precise Cutting Force Estimation by Hybrid Estimation of DC/AC Components

2020 ◽  
Author(s):  
Taiki Sato ◽  
Shuntaro Yamato ◽  
Yasuhiro Imabeppu ◽  
Naruhiro Irino ◽  
Yasuhiro Kakinuma
Keyword(s):  
Cutting Force ◽  
Thrust Force ◽  
End Milling ◽  
Moving Average ◽  
Low Frequency ◽  
Friction Model ◽  
Ball Screw ◽  
Estimation Accuracy ◽  
Force Estimation ◽  
Feed Direction

Abstract External sensor-less cutting force estimation using a load-side disturbance observer (LDOB) has potential to estimate the cutting force with high accuracy in both feed and cross-feed directions. However, the accuracy of its low frequency components in feed direction decrease due to effect of the friction and heat of a ball-screw-driven stage. In this study, DC and AC components of the cutting force is estimated by different methods; friction-compensated motor thrust force and LDOB, and the cutting force was estimated in real time by hybridizing them. In particular, regarding the friction model, the dynamic and static characteristics of the friction force in each axis (X, Y, Z) were identified from the idling test results. In addition to the model that depends on the velocity, the characteristics of the friction that depend on the position was also identified and considered when compensating for the motor thrust force. Then, a simple moving average filter with an appropriate window length is applied to the cutting force by LDOB and motor thrust force, and the DC component error of LDOB is corrected by that of motor thrust force. The validity of the proposed method was evaluated through end-milling tests. The experimental results showed that estimation accuracy of cutting force using the proposed method can be greatly improved in feed directions. On the other hand, in cross-feed direction, the cutting estimation was performed using the conventional LDOB.

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