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The accuracy for target tracking using a conventional interacting multiple-model algorithm (IMM) is limited. In this paper, a new variable structure of interacting multiple-model (VSIMM) algorithm aided by center scaling (VSIMM-CS) is proposed to solve this problem. The novel VSIMM-CS has two main steps. Firstly, we estimate the approximate location of the true model. This is aided by the expected-mode augmentation algorithm (EMA), and a new method—namely, the expected model optimization method—is proposed to further enhance the accuracy of EMA. Secondly, we change the original model set to ensure the current true model as the symmetry center of the current model set, and the model set is scaled down by a certain percentage. Considering the symmetry and linearity of the system, the errors produced by symmetrical models can be well offset. Furthermore, narrowing the distance between the true model and the default model is another effective method to reduce the error. The second step is based on two theories: symmetric model set optimization method and proportional reduction optimization method. All proposed theories aim to minimize errors as much as possible, and simulation results highlight the correctness and effectiveness of the proposed methods.

During the working process of the ADN-based thruster, continuously, heat generated by the chemical reaction in the combustion chamber will transfer along the upstream capillary, the propellant in the capillary continuously absorbs heat under the effect of heat transfer from the wall and undergoes a phase change when the saturation temperature is reached. In this study, effects of the downstream heating temperature (623 K to 923 K) on mass flow rate and pressure change in the capillary were investigated based on the established test platform. Simultaneously, the VOF (volume of fraction) model, and the Lee phase transition model coupled with the Navier–Stokes method was utilized to simulate the spatial distribution of the gas-liquid propellant in the capillary. The results show that the ADN-based propellant firstly formed bubbles on the inner wall surface near the exit of the capillary, and these vapor bubbles moved and grew upstream along the capillary. Due to the cooling effect of the ADN-based propellant inflow, the temperature distribution of the front chamber and capillary gradually reached equilibrium. Bubbles were constantly generated in the capillary, and as the heat reflux intensified, the total volume of bubbles in the capillary continued increasing. Single-phase flow, annular flow, wave flow, and segment plug flow appeared sequentially along the axial direction of the capillary, and the proportion of gas phase volume fraction at the capillary outlet section gradually increased.

Laguerre spatial–temporal processing is a well-known method used to design a wideband beamformer. In this paper, a generalized wideband reduced-rank Laguerre beamformer (RRLB) is proposed. The RRLB uses a reduced-rank transform matrix to estimate the signal subspace and reduces the scale of the received data, which reduces the complexity of obtaining the adaptive weights. The reduced-rank matrix is usually constructed by the eigenvector of the covariance matrix, while the eigenvectors are obtained via eigen-decomposition with a high computational load. To reduce the complexity of eigen-decomposition, a fast reduced-rank Laguerre beamforming (FRRLB) algorithm is proposed. In the estimated covariance matrix case, a set of received data vectors is used to construct the reduced-rank matrix for an approximate but fast estimate of the interference subspace. With undistorted response to the desired signal and satisfactory anti-jamming capability, the FRRLB reduces the computational complexity of the adaptive weight approach. The simulation results highlight the validity and effectiveness of the proposed methods.

Sub-band adaptive processing is an established method to design a broadband beamformer. The uniform decomposition method (UDM) is a common approach for designing sub-band adaptive beamformer (SAB) that would split the received signal into a number of uniform sub-bands. However, the UDM has redundancies on decomposed sub-bands at high frequencies in the passband. In this paper, we propose a number of techniques to overcome this issue. By proposing a novel relative bandwidth method (RBM), we obtain that the relative bandwidth of each sub-band is the same. Using this as a basis, we present a non-uniform decomposition method (NUDM) such that the NUDM has fewer sub-bands than the conventional UDM, leading to reduced computational complexity. We also propose an elegant metric, adjacent bandwidth ratio (ABR), to facilitate easier comparison of non-uniformity. We then extend NUDM method to provide a fast variant of the non-uniform decomposition SAB (FNUD-SAB). We ensure that the sub-band frequencies and corresponding adaptive weights are available as part of the proposed FNUD-SAB method. With undistorted response to the desired signal and effective anti-jamming capability, the new beamformer reduces the computational complexity by reducing the number of sub-bands. Simulation results highlight the effectiveness of the proposed methods.

Space-time generalised sidelobe canceller (GSC) is a well-substantiated method for broadband beamforming. In this paper, a generalised reduced-rank structure is established for the broadband space-time GSC. The generalised structure estimates signal subspace by a reduced-rank transform matrix, and so the dimension of broadband signal data vector is decreased. Therefore, the computational complexity for obtaining the adaptive weights is reduced. Generally, the reduced-rank matrix is obtained by eigen-decomposition of the data covariance matrix, which is a large computational load for broadband space-time processing. A fast reduced-rank algorithm is then proposed for the generalised structure to rapidly construct the reduced-rank matrix and to alleviate the computational burden caused by eigen-decomposition. The signal subspace is rather robust to the received data, hence, a set of received data can be used to construct the reduced-rank matrix for a rough and fast estimate of the signal subspace. With the undistorted response to signals of interest and the satisfactory anti-interference capability, the proposed algorithm could effectively reduce the computational complexity of the adaptive weight approach. Simulation results highlight the correctness and effectiveness of the proposed methods. HighlightsA new low-complexity space-time generalised sidelobe canceller (GSC) and its fast algorithm are proposed in this study.The GSC uses the reduced-rank matrix to estimate the signal subspace.The received data vectors are used to rapidly form the reduced-rank matrix.The singular value decomposition operation for the frequency domain constraints is applied to the novel algorithm.