Optimal Order of Time-Domain Adaptive Filter for Anti-Jamming Navigation Receiver

Adaptive filtering algorithms can be used on the time-domain processing of navigation receivers to suppress interference and maintain the navigation and positioning function. The filter length can affect the interference suppression performance and hardware utilization simultaneously. In practical engineering, the filter length is usually set to a large number to guarantee anti-jamming performance, which means a high-performance receiver requires a high-complexity anti-jamming filter. The study aims at solving the problem by presenting a design method for the optimal filter order in the time-domain anti-jamming receiver, with no need for detailed interference information. According to interference bandwidth and jam-to-signal ratio (JSR), the approach designed a band-stop filter by Kaiser window for calculating the optimal filter order to meet interference suppression requirements. The experimental results show that the time-domain filtering processing has achieved good interference suppression performance for engineering requirements with optimal filter order in satellite navigation receivers.

An Azimuth Signal-Reconstruction Method Based on Two-Step Projection Technology for Spaceborne Azimuth Multi-Channel High-Resolution and Wide-Swath SAR

Azimuth non-uniform signal-reconstruction is a critical step for azimuth multi-channel high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) data processing. However, the received non-uniform signal has noise in the actual azimuth multi-channel SAR (MCSAR) operation, which leads to the serious reduction in the signal-to-noise ratio (SNR) of the results processed by a traditional reconstruction algorithm. Aiming to address the problem of reducing the SNR of the traditional reconstruction algorithm in the reconstruction of non-uniform signal with noise, a novel signal-reconstruction algorithm based on two-step projection technology (TSPT) for the MCSAR system is proposed in this paper. The key part of the TSPT algorithm consists of a two-step projection. The first projection is to project the given signal into the selected intermediate subspace, spanned by the integer conversion of the compact support kernel function. This process generates a set of sparse equations, which can be solved efficiently by using the sparse equation solver. The second key projection is to project the first projection result into the subspace of the known sampled signal. The secondary projection can be achieved with a digital linear translation invariant (LSI) filter and generate a uniformly spaced signal. As a result, compared with the traditional azimuth MCSAR signal-reconstruction algorithm, the proposed algorithm can improve SNR and reduce the azimuth ambiguity-signal-ratio (AASR). The processing results of simulated data and real raw data verify the effectiveness of the proposed algorithm.

Examination of the Non-Orthogonal Multiple Access System Using Long Short Memory Based Deep Neural Network

This paper investigates deep learning (DL) non-orthogonal multiple access (NOMA) receivers based on long short-term memory (LSTM) under Rayleigh fading channel circumstances. The performance comparison between the DL NOMA detector and the traditional NOMA method is established, and results have shown that the DL-based NOMA detector performance is far better in comparison with conventional NOMA detectors. Simulation curves are compared with the performance of the DL detector in terms of minimum mean square estimate (MMSE) and least square error (LSE) estimate, taking all realistic circumstances, except the cyclic prefix (CP), and clipping distortion into account. The simulation curves demonstrate that the performance of the DL-based detector is exceptionally good when it equals 1 when the noise signal ratio (SNR) is more than 15 dB, assuming that the DL method is more resilient to clipping distortion.

Consistency of noncognitive skills and their relation to educational outcomes in a UK cohort

Noncognitive skills have been shown to associate with a range of health and socioeconomic outcomes. Many studies have relied on cross sectional data and have been unable to assess the longitudinal consistency of noncognitive skill measures. Using data from a UK birth cohort, we investigated a range of noncognitive skills: behavioural problems, social skills, communication, self-esteem, persistence, locus of control, empathy, impulsivity and personality. We assessed their consistency over a 17-year period throughout childhood and adolescence (age 6 months to 18 years), their genomic architecture, and their associations with socioeconomic outcomes. We found high longitudinal measurement consistency for behavioural and communication skills, but low consistency for other noncognitive skills, suggesting a high noise to signal ratio. We observed consistent non-zero heritability estimates and genetic correlations for only behavioural difficulties. Using aggregate measures of each skill over time, we found evidence of phenotypic correlations and heritability ($$h_{SNP}^2$$ h S N P 2 = 0.1–0.2) for behaviour, communication, self-esteem and locus of control. Associations between noncognitive skills and educational outcomes were observed for skills measured in mid to late childhood but these were at most a third of the size of IQ-education associations. These results suggest that measures designed to capture noncognitive skills may be subject to considerable response heterogeneity or measurement error. Aggregate measures that leverage repeat responses from longitudinal data may offer researchers more reliable measures that better identify underlying noncognitive skills than cross sectional measures.

Speckle Noise Detection and Removal for Laser Speech Measurement Systems

Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are easily affected by complex detection environments. Thus, speckle noise often appears in the measured speech, seriously affecting its quality and intelligibility. This paper examines all of the characteristics of impulsive noise in laser measured speech and proposes a novel automatic impulsive noise detection and removal method. This method first foregrounds noise using decorrelation based on a linear prediction (LP) model that improves the noise-to-signal ratio (NSR) of the measured signal. This makes it possible to detect the position of noise through a combination of the average short-time energy and kurtosis. The method not only precisely locates small clicks (with a duration of just a few samples), but also finds the location of longer bursts and scratches (with a duration of up to a hundred samples). The located samples can then be replaced by more appropriate samples whose coding is based on the LP model. This strategy avoids unnecessary processing and obviates the need to compromise the quality of the relatively large fraction of samples that are unaffected by speckle noise. Experimental results show that the proposed automatic speckle noise detection and removal method outperforms other related methods across a wide range of degraded audio signals.

ESTIMATION METHODS OF A CHANNEL WITH SPATIAL MODULATION BASED ON CORRELATION

Рассматриваются методы оценки канала связи с пространственной модуляцией. Данный вид модуляции представляет собой методику однопотоковой передачи данных с несколькими входами и несколькими выходами (MIMO), при которой одновременно активируется только одна передающая антенна. Пространственная модуляция позволяет добиться полного исключения межканальных помех, а также демонстрирует большую экономию энергии в радиочастотной цепи. Однако, в отличие от многопоточных систем MIMO, оценка канала для пространственной модуляции становится проблемой, поскольку канал MIMO не может быть оценен на одном этапе передачи по единственному потоку. На основании этого факта была предложена новая схема оценки канала, которая использует корреляцию каналов и совместно оценивает каналы для разных передающих антенн. Предложенный метод обеспечивает тот же период оценки, что и многопоточные схемы MIMO. Исследовано изменение количества передаваемых пилот-сигналов при пространственной модуляции как для традиционных, так и для новых методов оценки канала связи. Уравновешивая точность и объем данных, можно достичь оптимального отношения пилот-сигналов для максимальной пропускной способности канала. Результаты моделирования показывают, что новый подход оценки превосходит традиционный метод с гораздо более низким оптимальным коэффициентом количества пилотов The article considers methods for estimating a communication channel with spatial modulation. This type of modulation is a single-stream multiple-input multiple-output (MIMO) technique in which only one transmit antenna is activated at a time. Spatial modulation allows for complete elimination of inter-channel interference, and also demonstrates great energy savings in the RF circuit. However, unlike multi-stream MIMO systems, channel estimation for spatial modulation becomes a problem because a MIMO channel cannot be estimated in a single transmission step on a single stream. Based on this fact, I proposed a new channel estimation scheme that uses channel correlation and jointly estimates channels for different transmit antennas. The proposed method provides the same evaluation period as multithreaded MIMO schemes. The change in the number of transmitted pilot-signals with spatial modulation is investigated for both traditional and new methods of estimation of the communication channel. By balancing accuracy and data volume, an optimal pilot signal ratio can be achieved for maximum channel throughput. Simulation results show that the new scoring approach outperforms the traditional method with a much lower optimal pilot count ratio