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The effect of jammer on radar or jamming performance has been and is being assessed on the basis of range reduction where consistency in tracking target ability is more important than range reduction in a tracking radar. A new criterion known as relative radar functionality destruction time is defined and introduced as the relative of functionality destruction time of radar to one period of jammer, where jammer signal and target echo power are of concern. The effective parameters in relative time of the receiver functioning destruction are assessed. Next, this criterion is applied in the assessment of simple conical scan radar receiver against a conventional jamming (sweep noise jamming). This criterion is modeled and simulated on a search radar in the jamming environment where the minimum required standard deviation of noise for destroying the radar function yields. By implementing the structure of a frequency modulated continuous wave tracking radar structure, a simple target based on digital radio frequency memory method and one type of jamming against this radar in a simultaneous manner, the functionality destruction is extracted for different radar parameters. This new criterion on outperforms its counterparts. [ABSTRACT FROM AUTHOR]

Controlling peak side-lobe level (PSL) is of great importance in high-resolution applications of multiple input multiple output (MIMO) radars. In this paper, designing sequences with good autocorrelation properties are studied. The PSL of the autocorrelation is regarded as the main merit and is optimized through newly introduced cyclic algorithms, namely, PSL minimization quadratic approach, PSL minimization algorithm where the smallest rectangular, and PSL optimization cyclic algorithm. It is revealed that minimizing PSL results in better sequences in terms of autocorrelation side lobes when compared with traditional integrated side-lobe level minimization. In order to improve the performance of these algorithms, fast-randomized singular value decomposition is utilized. To achieve waveform design for MIMO radars, this algorithm is applied to the waveform generated from a modified Bernoulli chaotic system. The numerical experiments confirm the superiority of the newly developed algorithms compared to high-performance algorithms in monostatic and MIMO radars. [ABSTRACT FROM AUTHOR]

The most important goal of spreading spectrum communication system is to protect communication signals against interference and exploitation of information by unintended listeners. In fact, low probability of detection and low probability of intercept are two important parameters to increase the performance of the system. In Direct Sequence Code Division Multiple Access (DS-CDMA) systems, these properties are achieved by multiplying the data information in spreading sequences. Chaotic sequences, with their particular properties, have numerous applications in constructing spreading codes. Using one-dimensional Bernoulli chaotic sequence as spreading code is proposed in literature previously. The main feature of this sequence is its negative auto-correlation at lag of 1, which with proper design, leads to increase in efficiency of the communication system based on these codes. On the other hand, employing the complex chaotic sequences as spreading sequence also has been discussed in several papers. In this paper, use of two-dimensional Bernoulli chaotic sequences is proposed as spreading codes. The performance of a multi-user synchronous and asynchronous DS-CDMA system will be evaluated by applying these sequences under Additive White Gaussian Noise (AWGN) and fading channel. Simulation results indicate improvement of the performance in comparison with conventional spreading codes like Gold codes as well as similar complex chaotic spreading sequences. Similar to one-dimensional Bernoulli chaotic sequences, the proposed sequences also have negative auto-correlation. Besides, construction of complex sequences with lower average cross-correlation is possible with the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a study of hard combination data fusion for cooperative spectrum sensing in Cognitive Radio (CR). Fast and accurate spectrum sensing is crucial in realizing a reliable cognitive network. Cooperative spectrum sensing can help reducing the mean detection time and increasing the agility of the sensing process. However, when the number of cognitive users is large, the bandwidth need for the control channel that are used to report the secondary user nodes' results to the fusion center may become excessively large. This paper presents a hard decision-based cooperative sequential detection scheme to reduce the average sensing time that is required to reach a detection decision. In the scheme, each cognitive radio computes the log likelihood ratio for its every measurement, and quantizes its measurements then sends its hard-decision to base station and the base station sequentially accumulates these log likelihood statistics and determines whether to stop making measurement. [ABSTRACT FROM AUTHOR]

Surface electromyography (SEMG) from respiratory muscles is a non-invasive and effective method of studying neuromuscular diseases, muscle fatigue, enhancement of muscular function and also human-computer interface. This signal is contaminated by different noises. These include environmental noises like power line noise and also internal noises such as electrocardiographic noise. The clean EMG signal can be extremely useful for pathological purposes. In this study, diaphragmatic EMG signals were recorded with Power Lab system from seven subjects. The signals showed contamination due to power line interference (PLI) and also cardiac activity. Adaptive filters were used to reduce cardiac noise as well as 50 Hz (the fundamental) power line noise and its harmonics. Recursive least squares algorithm was used for the structure of the adaptive filter. Different values of the filter parameters; filter order and forgetting factor were examined for the noise removal purpose. Performance of the adaptive filter was quantified by signal-to-noise ratio and coherence measures for simulated data. The results show that we can successfully eliminate PLI and ECG noise from SEMG signals with adaptive filters. The figures and tables obtained help to decide which parameters of the filter are the best for our study. [ABSTRACT FROM AUTHOR]