Electronics Letters最新文献

Target localization for distributed radars requires precise knowledge of the calibration errors in time, frequency, and space. Previous studies focus on the sensor location error and sensor directional error in space. This paper concentrates on the system errors in time and frequency which directly affect the targets estimation of range and velocity. Based on linear frequency modulation waveform, the impact of the system errors including sample interval, pulse repetition interval, and centre frequency are analysed. An alternating optimization algorithm is proposed to achieve the target localization, velocity estimation and system errors estimation simultaneously. Simulation shows the effectiveness of the algorithm and the influence on localization due to varying number of targets and radars.

In a drone system with dual data links, this article presents a redundant data processing algorithm that can minimize flight control instability without increasing the weight and price of the aircraft by software processing of duplicate received messages.

A four-degree-of-freedom upper limb exoskeleton rehabilitation robot system with a gravity compensation device is constructed. The objective is to address the rehabilitation training needs of patients with upper limb motor dysfunction. A BP neural network adaptive control method based on particle swarm optimization is proposed. First, the degrees of freedom of the human body are analyzed, and a Lagrange method is employed to construct a dynamic model. Second, a particle swarm optimization back propagation neural network adaptive control algorithm based on particle swarm optimization is presented. Subsequently, the range of motion of the upper limbs is analyzed with reference to muscle anatomy and a three-dimensional motion capture system. And the robot structure design is analyzed in detail. Finally, simulation experiments were conducted, and the results demonstrated that the proposed method exhibited high effectiveness and accuracy.

This letter presents the design of a 13.56 MHz offset-enhanced full-wave active rectifier, tailored for wirelessly powered biomedical implants. The design incorporates digitally assisted, delay-compensated active diodes and symmetrical bulk biasing in the rectifier core to enhance conduction time, thus improving the voltage conversion ratio (VCR) and power conversion efficiency (PCE). A delay improvement is achieved both in no-load and high-load conditions through an additional comparison path with an offset voltage that is higher than zero. The proposed rectifier is implemented and fabricated in a 180 nm CMOS technology with an area of 0.024 $�{\text{mm}}^2$. The rectifier, tested and measured with inductive links, offers a maximum VCR of 96.4% and a maximum PCE of 89%.

Locality preserving projection (LPP) is a typical feature extraction method based on spectral information for hyperspectral image (HSI) classification. Recently, to improve the classification performance, the spatial information of HSI has been applied in the LPP method. However, for most of spatial–spectral-based LPP methods, they explore the spatial–spectral information within a fixed local window, which cannot be appropriate to the irregular-shape ground objects in HSI. To over this issue, an effective superpixel-guided LPP and spatial–spectral classification method are proposed, in which the spatial–adaptive structure information is fully excavated for HSI classification. Specifically, superpixel segmentation is first conducted on the HSI to generate shape-adaptive homogeneous subregions. Then, to learn more discriminative projection, the neighbourhood graph for LPP is constructed based on spatial–spectral similarity, in which pixels within the same superpixel are connected. Finally, the obtained projection feature is input a classifier to yield the initial classification result, and the edge information of ground objects captured by superpixels is utilized to optimize the initial classification result. Experiments on two real hyperspectral datasets demonstrate that the proposed superpixel-guided and spatial–spectral classification method significantly outperforms the other well-known techniques for HSI classification.

The integration of renewable energy into power grid planning poses significant challenges. In this investigation, planning strategies across eight key indicators encompassing economic, reliability, environmental, and adaptability are assessed. Leveraging the analytical hierarchy process alongside the entropy weight method, subjective and objective weights are ascertained and comprehensive weights with parsimonious discriminative data are synthesized. Scores for planning strategies are then derived utilizing these weights. To illustrate and validate the efficacy of the proposed methodology, it was applied to four schemes within the IEEE-6 node system, incorporating wind and photovoltaic power plants.

Distribution system (DS) communication failures following extreme events often degrade monitoring and control functions, thus preventing the acquisition of complete global DS component state information, on which existing post-disaster DS restoration methods are based. This paper proposes methods of inferring the states of DS components in the case of incomplete component state information. By using the known DS information, the operating states of unobservable DS branches and buses can be inferred, providing complete information for DS performance restoration before full communication recovery.

This letter proposes a novel planar endfire circularly polarized antenna with widened half-power beamwidth. Widened azimuth beamwidth mechanism of 2D sectorial electric dipole is theoretically revealed, thus it is able to combine with a rectangular magnetic dipole to yield a half-power beamwidth widened planar endfire circularly polarized antenna. Finally, a prototype planar endfire circularly polarized antenna with sectorial flared angle of α = 270° is fabricated, simulated, and implemented to validate the design approach. As investigated, the antenna exhibits broadened azimuth half-power beamwidth of 150° over a frequency range of 2.40–2.45 GHz.

Due to the nonlinear nature of continuous phase modulation (CPM), most existing unambiguous acquisition algorithms are ineffective in eliminating the ambiguity threat faced by semi-integer CPM signals. To address this issue, this letter proposes an unambiguous acquisition algorithm based on sub-correlation functions combination (SCFC). The main idea of this algorithm is to decompose the first pulse amplitude modulation waveform derived from the Laurent decomposition into sub-signal waveforms that are appropriate for CPM signals. The final unambiguous function is obtained by combining the autocorrelation function of the received CPM signal with the sub-correlation functions derived from the sub-signal waveforms and the received CPM signal. Simulation results demonstrate that the SCFC algorithm can eliminate the ambiguity threat of semi-integer CPM signals with relatively minor detection loss. Moreover, the proposed algorithm successfully retains a narrow main peak and exhibits superior multipath resistance.

During terminal guidance, the attack platform is provided with a high-resolution image of the target area through the application of synthetic aperture radar. Additionally, the stealth trajectory with low observability can significantly impact mission success. This paper considers both the performance of missile-borne synthetic aperture radar imaging and stealth performance as influencing factors for terminal trajectory optimization, which is modelled as a constrained multi-objective optimization problem. The application of the pseudospectral method in the solution of optimal control problems has led to the proposal of the hybrid genetic algorithm pseudospectral optimization framework. The problem is decomposed into several single-objective optimal control problems, which can generate a specific initial population for the genetic algorithm to obtain a set of Pareto-optimal solutions. Finally, the numerical simulations demonstrate the effectiveness of the proposed optimization approach compared with the benchmark scheme.