Abstracts:In [1], Algorithm 1 on p. 5007 should appear this way. Algorithm 1: Attitude Estimation From Weights in Case of Symmetries.

Abstracts:To address the problem of weak moving target detection, this article proposes a maximum eigenvalue (ME)-based multiframe track-before-detect (TBD) method to implement multiframe integration and enhance target detection performance. Specifically, the MEs of Hermitian positive-definite matrices for the intraframe radar echo signals are used to form an ME detector, and the performance of the detector is guaranteed by the generalized likelihood ratio test. Then, to integrate interframe target information, we apply an efficient dynamic programming (DP) algorithm, for which the scoring function is derived by designing an ME-based multitask optimization scheme. As a consequence, an ME-based DP-TBD method is developed, which does not rely on any prior knowledge about the target and the clutter. The advantages of the proposed method are validated through experiments utilizing both simulated data and real radar data. The results show that the proposed method obtains better performance in comparison with the state-of-the-art methods.

Abstracts:This article investigates the librational motion control problem of the tethered space-tug (TST) system in the process of deorbiting space debris. By analyzing the dynamic equations of the TST system, the librational motion control problem of the system in 3-D space can be transcribed to librational motion control problems inside and outside the orbital plane. The motion of the TST system inside or outside the orbital plane can be properly characterized through a highly simplified ring-string (R-S) model, which can be properly analyzed using the finite time-domain wave equation. An absorbing excitation method is proposed to suppress the librational motion of the R-S model, where the librational motion suppression control is achieved by offsetting the equivalent excitation obtained through motion analysis. Different from wave-based controls, which ignore the mass of execution structure, the effect of the mass of the tug and target on the control rate is compared through numerical simulations of four control rates based on the absorbing excitation method.

Abstracts:Frequency diverse array (FDA) radar enjoys a remarkable benefit in range ambiguous clutter suppression thanks to its range dependency of transmitting beam pattern. However, a linear frequency offset can cause secondary range ambiguity problems that deteriorate the clutter suppression performance. To address this problem, we propose here a nonlinear frequency offset optimization strategy for planar FDA-space time adaptive processing radar. In this article, our study first formulates a space-time-range signal model of a planar FDA radar. Based on the analysis of the secondary range ambiguity, we address the nonlinear frequency offset optimization problem and propose an improved search algorithm with fast convergence to solve it. Numerical analysis is carried out to verify the validity of the proposed nonlinear strategy to remove the secondary range ambiguity problem and maintain a high range-dimensional beam resolution.

Abstracts:The transfer function approach (TFA) extensively developed by many authors has resulted in several robust filtering algorithms for linear disturbed electronic systems. Taking a fresh look at the problem, this article uses TFA to determine the bias correction gain for the recursive energy-to-energy $H_\infty$-Kalman filter (KF). The gain is shown to range between the higher gain of the optimal KF and the lower gain of the robust unbiased finite impulse response (UFIR) filter. Accordingly, $H_\infty$-KF produces an intermediate mean square error and has an intermediate robustness and estimation quality. An experimental example of tracking using ultrawideband technology has revealed that $H_\infty$-KF is also able to outperform both the KF and UFIR filter.

Abstracts:Based on an open radio access network (O-RAN) architecture in terrestrial networks (TNs), this study proposed an open nonterrestrial network (open NTN) architecture, in which multiple service operators could share low Earth orbit (LEO) satellites for cost-effective network deployment in LEO-based NTNs. In the open NTN, a centralized unit of next-generation node B is located in a gateway, and the distributed units and radio units are in LEO satellites. Intersatellite links (ISLs) between LEOs function as wireless fronthaul links, where data and pilot symbols are delivered for further processing. Compared to O-RAN in TNs with wired fronthaul, the bandwidth constraints in wireless ISL fronthaul are more stringent, and signal compression in fronthaul cannot be avoided. Therefore, to improve the efficiency of open NTNs, a joint optimization problem of ISL fronthaul compression rate and power allocation to the data and pilot signals was formulated to maximize the sum of uplink rates of multiple user equipments under the bandwidth constraints of the ISL fronthauls. The original problem was divided into two subproblems: one is an optimization of the data and pilot compression rate and the other is that of the data and pilot power allocation. An alternating optimization approach that solved two subproblems in an iterative manner was adopted to find the convergent near-optimal solution. The convergence and performance of the proposed approach were verified with numerical results.

Abstracts:The joint selection of subarrays and operational mode plays a crucial role in distributed coherent aperture radar with multiple subarrays, which has received limited attention despite its significance in multitarget tracking. We model the joint selection problem of subarrays and operational mode as a restless multiarmed bandit (RMAB) process, aiming to minimize the expected total discounted error covariance trace value over an infinite time horizon. This article generalizes the conventional binary-action RMAB to the more complex multiaction RMAB (MA-RMAB) process with multiconstraints. The Whittle relaxation with two distinct Lagrange multipliers is utilized to relax the constraints on subarrays and computing resources over an infinite time horizon. A multiindex policy is proposed as a computable suboptimal heuristic for the MA-RMAB model, where the multiindexes are calculated by using the optimal value of the Lagrangian dual problem. The effectiveness of the proposed multiindex policy is validated through numerical simulation.

Abstracts:In the directional antenna element-based uniform arc array (DA-UAA), the conventional spatial spectrum estimation algorithms such as multiple signal classification could not be utilized to find the direction-of-arrival (DOA) of an incident electromagnetic wave because of the incomplete information about the radiation pattern and polarization characteristics of each array element. In this article, a collection of DOA estimation algorithms for cases with incomplete DA-UAA manifold information is proposed. First, the received signal model of the DA-UAA is analyzed, and an active calibration method for array receivers, incorporating de-embedding equalization filtering to address the interchannel amplitude and phase inconsistencies, is proposed. Based on the traditional omni-directional amplitude-comparison DOA estimation method, the cosine-series expansion-based multiantenna amplitude-comparison DOA estimation method is adopted by the DA-UAA. Second, the low-order Legendre polynomial-based difference-sum amplitude-comparison DOA estimation algorithm and the Legendre-series-based root-seeking amplitude-comparison DOA estimation method are proposed to combine computational complexity and direction-finding accuracy. Third, an eigen subspace projection-based successive suppression amplitude-comparison DOA estimation strategy is designed to handle multiple incident waves with the same frequency. Finally, the effectiveness and accuracy of these proposed algorithms are verified through numerical simulations and field experiments, with the Cramér-Rao Lower Bound analyzed simultaneously.

Abstracts:This article proposes an intelligent frequency agile strategy design for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several nonoverlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multiagent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile strategy design, a joint coalition formation game and distributed Q-learning algorithm is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies.

Abstracts:In this article, a long-time coherent integration approach is proposed for a maneuvering target with jerk. In this approach, the third-order keystone transform is first employed to correct the cubic range migration induced by jerk. Then, the centrosymmetric transform, scaled inverse Fourier transform, and nonuniform fast Fourier transform (NUFFT) are executed sequentially to accomplish the velocity and acceleration estimation. Thereafter, based on the estimated parameters, the phase compensation function is constructed to remove the influences of velocity and acceleration terms. Based on this, the inverse fast Fourier transform (IFFT) and the NUFFT are performed to accomplish coherent integration in the range–jerk domain. Moreover, a comprehensive discrimination procedure is proposed to identify potential spurious peaks formed by cross components in the case of multitarget scene. Compared with the keystone transform and matched filtering, the proposed method can be efficiently implemented thanks to the avoidance of multidimensional grid search. In contrast with the conventional correlation-based methods, the proposed approach may achieve better antinoise performance attributed to involving only one nonlinear operation. Therefore, the presented approach may strike a good equilibrium between antinoise capability and computational load. Simulation and real measured data processing results prove the effectiveness of the presented method.