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Abstract In the digital era, realising intelligent digital transformation is a major challenge in the manufacturing field. Digital transformation means bringing more profit appreciation. To improve the analysis reliability of value‐added processes, this study proposes a method for assessing enterprises value‐adding activities. For this purpose, a hybrid model is constructed based on data and mathematics, bridged by a server. The research builds an element group model that identifies data from different sources, and also gives a mathematical model to describe the relationship of the supply, marketing and service. Taking an automobile manufacturing value chain as an example, to theoretically analyse the composition of value‐added activities. Then, the assembly process of an automobile manufacturing plant was used as a value‐added case study. The simulation results show the impact of changing production layout and product handling angle on the whole value chain. The study can provide new ideas for the intelligent digital transformation of the manufacturing industry.

Abstract Suppressing false alarms without impacting detection rate is an essential issue for search radars. Traditional threshold detection methods identify true targets by simply comparing the energy of target candidates with a threshold. In this work, a new data‐driven false‐alarm suppression approach is proposed based on a random forest model. It discriminates true targets and false alarms in the developed multi‐dimensional ambiguity feature spaces, instead of the time‐frequency features used in previous works, to fulfill short dwell‐time requirement of search radars. Evaluations through field experiments demonstrate that the proposed method can achieve as high as 98% validation accuracy and a significant improvement of detection performance compared to the conventional threshold detection.

The interest in microwave imaging system is increasing because it can serve as a useful tool for concealed threat detecting. The current imaging systems have two major challenges: (i) multi-static arrays suffer from complex hardware design and ineffective backprojection-imaging algorithm, and (ii) monostatic linear arrays suffer from large scanning time due to the electronically scanning one by one of the co-located receive–transmit antennas. To address these challenges, this study introduces a novel linear imaging array based on automotive radar chips and sub-array time-division multiple-input multiple-output working principles, which is hardware efficient and compatible fast Fourier transform (FFT) imaging technique. Through simulation, it is shown that the scanning time is only one-fourth of the traditional monostatic linear array and the FFT image reconstruction technique can be used.

The authors report a target separation detection and motion parameter estimation method based on the time-varying autoregressive (TVAR) model. The TVAR model is used to extract the instantaneous Doppler frequencies of multiple targets or scattering points in a same radar range cell, and the motion parameters are estimated based on the Doppler frequencies at every pulse time in a radar frame. In particular, for coherent multipulse echo signal, the TVAR model is first utilised to extract multiple instantaneous Doppler frequencies at each pulse time, thus forming a Doppler frequency matrix. Second, the Doppler tracking and polynomial fitting methods are utilised to estimate the radial velocity and acceleration based on the Doppler frequency matrix. Finally, the target separation detection is achieved by acquiring and validating multiple Doppler frequency components in the same range cell. Simulations and verifications are carried out, and the results show that the proposed method is effective for target separation detection and precision motion parameter estimation, which could be of great value radar target detection, tracking, and automatic target recognition.

This study dealt with the fault-tolerant cooperation problem for a class of time-varying multi-vehicle system with actuator faults under the mixed [inline-formula] structure. Through solving coupled backward Riccati equations, a distributed cooperation fault-tolerant controller was designed for satisfying the proposed [inline-formula] constraints. Finally, a numerical simulation verified the effectiveness of the proposed method.