Potential immunity of radio control lines

2021 ◽  
Author(s):  
N.M. Ashimov ◽  
A.S. Vasin ◽  
A.N. Birukov ◽  
P.G. Kuzmishchev
Keyword(s):  
Signal Processing ◽  
Noise Immunity ◽  
Matched Filter ◽  
Input Circuit ◽  
Signal Spectrum ◽  
Radio Link ◽  
Control Line ◽  
Input Noise ◽  
Signal Suppression ◽  
Signal Channel

In the work, a methodology for assessing the potential noise immunity of radio control lines operating with binary FT signals is presented when using both element-by-element signal processing and signal processing in toto. The calculation method is based on the criterion adopted in radio control lines. According to the proposed technique, calculation shows that potential noise immunity with element-by-element signal processing is achieved with coherent reception of the FT signal under conditions of an unlimited increase in the code width, therefore, the frequency band occupied by the signal is expands indefinitely. In this case processing a binary signal in toto is realized by transferring the clipper from the video channel to the input signal receiving circuit. The transition from element-by-element signal processing to processing it in toto accompanied by an increase in the maximum possible value of the noise immunity coefficient by a factor of / 2 . Such an effect, in comparison with the circuit of the model of the radio control line with element-by-element processing of the FT signal, is achieved due to the transfer of the clipper, which plays the role of a decisive element in the circuit when receiving a symbol, into the input circuit. As a result, a filter-clipper-filter system is formed together with bandpass F1 and F2 filters. Therein F1 filter is still tuned to the frequency of the FT signal and matched to its symbol, and the passband of F2 is much higher than the bandwidth of the matched filter so that only the first harmonic of the signal spectrum is isolated without distortion practically. In this case, the clipper (O) ensures that the probability of false reception Pl is independent of the level of input noise, and at the s-n ratio q≤1 the clipper behaves like a linear device, while it is a classical nonlinear device when it is operating in the video signal channel (fig. 2) where there is signal suppression by interference which leads to a certain decrease in the potential radio link noise immunity during signal processing in element-by-element type.

INCREASED NOISE IMMUNITY COMMAND RADIO LINK SIGNALS WITH OFDM

2021 ◽  
pp. 7-20
Author(s):  
A. V. Leushin
Keyword(s):  
Noise Immunity ◽  
Relative Phase ◽  
Radio Link ◽  
Control Line ◽  
Radio Lines ◽  
Ability To Work ◽  
Signal Noise ◽  
Ofdm Signals

Reviewed the work of the command radio link with OFDM signals, which implements a quasicorrelative reception phaseshift keyed signals without a timing that provides improved immunity system and the ability to work in low relations signal/noise at low requirements to stabilize the frequencies of the reference oscillators of transmitter and receiver. The noise immunity estimation of the proposed system in comparison with radio lines operating with signals of frequency telegraphy and relative phase telegraphy is given. The main problematic issues of building a command radio control line caused by the use of OFDM signals are revealed.

Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar

2011 ◽  
Vol 28 (12) ◽  
pp. 1581-1597 ◽  
Author(s):  
Christopher D. Curtis ◽  
Sebastián M. Torres
Keyword(s):  
Signal Processing ◽  
Phased Array ◽  
Matched Filter ◽  
Meteorological Data ◽  
Weather Radar ◽  
Meteorological Variable ◽  
Seamless Integration ◽  
Computational Burden ◽  
Phased Array Radar ◽  
Spatial Coverage

Abstract This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.

scholarly journals Parameter estimation and signal detection algorithm based on adaptive capture in non-cooperative communication

2021 ◽  
Vol 336 ◽  
pp. 04002
Author(s):  
Zilong He ◽  
Peng Sun ◽  
Kexian Gong ◽  
Hua Jiang
Keyword(s):  
Parameter Estimation ◽  
Signal Detection ◽  
Cooperative Communication ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Frequency Offset ◽  
Detection Algorithm ◽  
Estimation Accuracy ◽  
Signal Frequency ◽  
Signal Spectrum

Aiming at the problem that the frequency offset in the non-cooperative communication system causes the received signal spectrum to shift, which exceeds the passband of the matched filter and affects the subsequent demodulation, a parameter estimation and signal detection algorithm based on adaptive capture is proposed by this paper, which is more convenient for hardware implementation and consumes less resources. The algorithm is divided into three parts. Firstly, use the correlation value between the signal and the preamble sequence as the basis for frequency capture. Secondly, the frequency is accurately estimated based on the interpolation algorithm. Finally, the phase-locked loop structure is used to track the frequency according to the characteristics of the frequency gradually changing and the signal frequency offset is eliminated in the Digital Down Converter stage. It provides necessary conditions for accurate signal detection and phase estimation. The simulation results show that the algorithm has high estimation accuracy, wide esti-mation range and low complexity. It can also achieve better estimation accuracy and detection performance under low signal-to-noise ratio.

scholarly journals A Modified Range Migration Algorithm for FMCW SAR Signal Processing

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Li Yake ◽  
Siu O’ Young
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Real Data ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Imaging Method ◽  
Memory Size ◽  
Processing Accuracy ◽  
Range Migration ◽  
Accurate Imaging

<p class="AbstractText"><span lang="EN-AU">The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.</span></p>

Signal Detection Technology for Giant Magnetoresistance Sensors

2013 ◽  
Vol 303-306 ◽  
pp. 270-273 ◽  
Author(s):  
Jing Hua Hu ◽  
Meng Chun Pan ◽  
Wu Gang Tian ◽  
Jia Fei Hu
Keyword(s):  
Signal Processing ◽  
Signal Detection ◽  
Giant Magnetoresistance ◽  
Low Noise ◽  
Output Data ◽  
Input Noise ◽  
Algorithm Efficiency ◽  
Detection Technology ◽  
Equivalent Input Noise ◽  
Signal Processing Methods

Presently, many attentions have been paid on low-noise pre-amplifier circuits and steady signal processing methods, but seldom on the combination of two technologies. In this paper, a small size low noise pre-amplifier circuit with 110dB Common Mode Rejection Ratio（CMRR）has been developed for giant magnetoresistance sensors(GMR) and its equivalent input noise voltage density is about . In addition, we proposed a new signal processing method for the sensors. In the method, we defined the quotient between the complex multiplex computation times and the output data num as a new figure of merit to evaluate that algorithm efficiency in signal detection, and name that quotient the computation times -to- output data num ratio (CTOR). Simulation results showed that the new method realized better parameters evaluation precision and higher efficiency than Modified Rife method, could be implemented easily in embedded systems.

The Influence of Modulation Voltage Flyback to LFMCW Radar’S Beat Signal

2011 ◽  
Vol 130-134 ◽  
pp. 1880-1884
Author(s):  
Jian Wei Leng ◽  
Fei An
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Frequency Component ◽  
Peak Detection ◽  
Beat Signal ◽  
Signal Spectrum ◽  
Radar Measurement ◽  
Distance Information ◽  
Modulation Voltage

This thesis focuses on the influence of VCO modulation voltage on LFMCW radar beat signal. Firstly, analysised the serious effect to beat signal spectrum caused by flyback voltage. Because of the false frequency component would be produced by voltage flyback. So that the radar measurement system can't be measured the correct distance information from the inaccurate peak detection. Thus, both digital signal processing and hardware produce synchronized signal are used to solve the bad influence by voltage flyback brought to LFMCW radar. Finally, compared the processing results with the null group, results shown that modulation voltage flyback would brought great difficulties on signal spectrum analysis, thus, the disturbance signal of flyback section should be processed during practice.

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