Template matching based on zero-mean normalized cross-correlation measure (ZNCC) has been widely used in a broad range of image processing applications. To meet the requirements for high processing speed, small size, and variable image size in automatic target recognition systems, a novel field-programmable gate array (FPGA)-based parallel architecture is presented in this paper for the ZNCC computation. The proposed architecture employs two groups of RAM blocks, one of which is used for the multiply-accumulate operations of the real and the reference images and the other for data rearrangement of the reference image, and their functions are switched through 2-input multiplexers when searching at the next row. Moreover, the sum of the pixels in the searching area of the real image is computed through serially accumulating the differences between the new column in the current searching area and the old column in the last searching area using one dual-port RAM. Simultaneously, the sum of the squares of the pixels is calculated in the same way. Using the Altera Stratix II FPGA chip (EP2S90F780I4) as the target device, the compilation results with Quartus II show that compared with the traditional architecture, the synthesis logic utilization decreases from 63% to 35% and the usage of DSP blocks decreases from 59% to 39%, while the memory bits only increase by 8% and the usage of other resources is nearly the same. The simulation and practical experimental results show that the proposed architecture can effectively improve the performance of the practical automatic target recognition system.

In this paper, an impedance control algorithm based on velocity for capturing two low impact docking mechanisms (LIDMs) is presented. The main idea of this algorithm is to track desired forces when the position errors of two LIDMs are random by designing the relationship between the velocity and contact forces measured by a load sensing ring to achieve low impact docking. In this paper, the governing equation of an impedance controller between the deviation of forces and velocity is derived, and simulations are designed to verify how impedance parameters affect the control characteristics. The performance of the presented control algorithm is validated by using the MATLAB and ADAMS software for capturing simulations. The results of capturing simulations demonstrate that the impedance control algorithm can respond fast and has excellent robustness when the environmental errors are random, and the contact forces and torques satisfy the low impact requirements.

The zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window technique, leveraging the Fourier Transform to precisely isolate the pedestrian’s gait frequency from spectral data. Building on this, the algorithm adaptively adjusts the zero-velocity detection threshold in accordance with the identified gait frequency. This adaptation significantly refines the accuracy in detecting zero-velocity intervals. Experimental evaluations reveal that this method outperforms traditional fixed-threshold approaches by enhancing precision and minimizing false positives. Experiments on single-step estimation show the adaptability of the algorithm to motion states such as slow, fast, and running. Additionally, the paper demonstrates pedestrian trajectory localization experiments under a variety of walking conditions. These tests confirm that the proposed method substantially improves the performance of the ZUPT algorithm, highlighting its potential for pedestrian navigation systems.

In contrast to classical zero-forcing (ZF) receiver, a new one called full-pilot zero-forcing (fpZF) receiver is exploited in our work. Based on this, we investigate the achievable uplink rate of a cell-free massive multi-input multi-output (MIMO) system with low-resolution analog-to-digital converters (ADCs) at the access points (APs). In order to carry out the tractable analysis on multiple quantization bits, we advocate the additive quantization noise model (AQNM). Quantization technology is a very effective method to lower the cost of transmission in the case where high data fidelity is not needed. After each AP receiving the payload data transmitted from all users, the quantization procedure is implemented in a distributed manner. Then a closed-form expression of achievable uplink rate is derived, which helps us to investigate system performance. The results in our simulation experiments indicate the fpZF receiver performs much better than the conjugate beamforming (CB) receiver when high-bit ADCs are used to process these received signals. However, when few-bit ADCs are adopted, its performance will decrease a lot and is dramatically inferior to the CB receiver, which is not as well as we expect. This observation demonstrates the fpZF receiver is more sensitive to the quantization operation than the CB receiver.

Exploring the lunar complex and extreme terrain presents formidable challenges for conventional lunar rovers. To address these limitations, this study proposes a novel hexapod jumping hybrid robot that incorporates a “figure-of-eight” (butterfly-shaped) six-branched wheel-legged mechanism and a jumping system that stores elastic energy via deformation of its elastic body. Inspired by the multimodal locomotion of grasshoppers, the robot dynamically switches between two operational modes: high-efficiency wheeled locomotion on relatively flat surfaces and agile jumping to traverse steep slopes and surmount large obstacles. A bio-inspired gait, inspired by the crawling patterns of a hexapod insect, is implemented using a Central Pattern Generator (CPG)-based controller to produce coordinated, rhythmic limb movements. Dynamic simulations of the jumping mechanism were conducted to optimize the critical parameters of the elastic structure and its associated control strategy. Experiments on a physical prototype were conducted to validate the robot’s wheeled mobility and jumping performance. The results demonstrate that the robot exhibits excellent adaptability to rugged terrains and obstacle-dense environments. The integration of multimodal locomotion and adaptive gait control significantly enhances the robot’s operational robustness and survivability in the harsh lunar environment, opening new possibilities for future lunar exploration missions.

The spectral analysis of the Doppler ultrasound signal has been widely used in medical diagnosis. The additional frequency components arising from noise will produce an adverse effect on the subjective study of the spectrogram and its quantitative analysis. To remove noise effectively, matching pursuits with three different time-frequency dictionaries including Gabor atoms (GMP), cosine packets (CMP), and wavelet packets (WMP) are proposed to remove noise from the quadrature Doppler ultrasound signal in this paper. The simulation results have shown that the GMP method can be best adapted to approximate the Doppler ultrasound signal with fewer atoms compared with the CMP and WMP methods, and this approach is also superior to the translation-invariant wavelet transform method. In contrast to the translation-invariant adapted local cosine transform, although the GMP method has achieved approximate performance improvements with higher computation intensity, it offers the potential advantages in pulsed Doppler ultrasound application because it have no requirement for the signal over-sample, which is needed in the traditional transform-based denoising methods in order to obtain a more precise estimation of the noise level.