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The multipeaked correlation functions of binary offset carrier (BOC) modulated signals introduce an ambiguity threat into the code tracking. Several techniques have been proposed to solve this problem, such as a class of two-dimensional (2-D) tracking techniques, in which the spreading code and the subcarrier are tracked separately. In this paper, the key properties of correlation functions and the theoretical tracking performance analysis considering noise and multipath environments of the general 2-D tracking loop are studied. Exact explicit expressions, taking into account the effects of local subcarrier waveform mismatching and the front-end bandlimiting, are provided for the correlation function employed in 2-D tracking. From these expressions, the key characteristics of 2-D correlation functions such as the shape, coupling relation between dimensions, and the effects of bandlimiting can be clearly seen. Moreover, general theoretical methods to predict the performance of the 2-D tracking techniques under the multipath and noise environments are provided. The results obtained in this paper can facilitate investigations in the area of 2-D tracking technique parameter optimization and performance assessment. [ABSTRACT FROM PUBLISHER]

Intentional jammers broadcasting chirp-style signals present a major threat to the operation of the global navigation satellite systems (GNSS) receivers. The time–frequency (TF) domain method based on the subspace projection technique is a common countermeasure against jamming. However, it is sensitive to inaccuracies in the instantaneous frequency (IF) estimates when dealing with jammers with rapidly changing frequency characteristics. In this paper, an approach for chirp-style jamming signal suppression in GNSS receivers using an adaptive-partitioned subspace projection is developed, which is insensitive to IF estimation errors. We first propose to choose the TF observation window length based on the jammer sweep rate and displace the IF estimates by a spectral bin to handle the resolution errors in the IF estimates. This operation ensures that the instantaneous phase (IP) estimation errors approximately stay constant for the interval that the jammer IF varies linearly upward. Owing to this property, the received data vector is partitioned into adaptive block sizes based on the jammer chirp rate estimates, which reflect the varying IF characteristics. The received signal is then projected onto the jammer orthogonal subspace constructed from the IF estimates according to the adaptive projection blocks. Simulation results indicate the effectiveness of the proposed technique for suppressing chirp-style jammers when compared with other techniques reported in the literature. The proposed approach provides an improvement by up to 11 dB in terms of the correlator signal-to-noise power ratio of the processed signal. [ABSTRACT FROM AUTHOR]

When a possible target is embedded in a low-rank (LR) Gaussian clutter (which is contained in a low-dimensional subspace) plus a white Gaussian noise, the detection process can be performed by applying the LR adaptive normalized matched filter (LR-ANMF), which is a function of the estimated projector. In a recent work, we derived an approximate distribution of the LR-ANMF under the $\mathcal {H}_0$ hypothesis by using a restrictive hypothesis (the target has to be orthogonal to the clutter subspace). In this paper, we propose to determine new approximations of the Pfa and the Pd of the LR-ANMF by relaxing this restrictive hypothesis. This new derivation is based on results concerning the convergence in a large dimension regime of quadratic forms. Simulations validate our result, in particular, when the tested signal is close to the clutter subspace. [ABSTRACT FROM AUTHOR]

Due to the need for adequate statistically homogeneous training, full-dimensional space-time adaptive processing (STAP) is well accepted to be impractical. Several previous works have addressed this issue by reducing the adaptive degrees of freedom (DoF), in turn reducing the required training. In this paper, we introduce a new multistage STAP approach that significantly reduces the required sample support while still processing all available DoF. The multistage fast fully adaptive (FFA) scheme draws inspiration from the butterfly structure of the fast Fourier transform. It uses a ?divide-and-conquer? approach by creating several smaller STAP problems but then combines the outputs of each problem adaptively as well. The reduction in required sample support rivals currently available reduced DoF algorithms. We also develop three variants of the algorithm, including one that uses random subdivisions of the original STAP problem.We test the efficacy of the algorithms developed via simulations based on simulated airborne radar data and measured high-frequency surface wave radar data. The results show that for simulated homogeneous data, the performance of the FFA approaches is comparable to that of available STAP algorithms; however, with measured data, the FFA approach provides significantly better performance. [ABSTRACT FROM AUTHOR]

This paper presents a detailed analysis of the dynamic behaviour of a hybrid ac-dc electric power system under large disturbances. The system under study is representative of a power distribution network which is currently being developed for future "more electric" aircraft (MEA). Brayton-Moser mixed potential is employed along with Lyapunov stability theorems to determine an analytical estimation of the large-signal stability boundary of the system. Extensive time- domain simulations using detailed behavioural models of the power system components are undertaken. It is shown that the analytically derived region of attraction agrees reasonably well with that obtained from the time-domain simulation. The predicted instability is experimentally validated. [ABSTRACT FROM AUTHOR]

The code measurement suffers from multiple error sources and especially multipath. The latter is unpredictable and changes in space and over time. Many interesting multipath mitigation techniques have been proposed. Most of them are not sufficiently effective for precise positioning using the code measurement. This paper presents a multipath insensitive delay lock loop that aims to improve the pseudorange measurement precision in the presence of multipath. This code loop is simple and does not require postprocessing of observables. Simulation and real implementation results showed that the proposed code loop dramatically improves the tracking error due to multipaths. Tracking error is limited to 1 m on pseudorange in typical multipath environments. This loop is more sensitive than the standard delay lock loop to thermal noise and applies predominantly to strong GNSS signals. [ABSTRACT FROM AUTHOR]

For a target with rotating parts, the ISAR image of its main body may be overshadowed by micro-Doppler signals, which are traditionally treated as interference and removed from radar echoes. However, it is potentially useful to perform imaging using micro-Doppler signals because they contain information on the geometrical structure of the rotating part. Inspired by the inverse Radon transform, well-known in the image processing community, this paper creates a data-recording model for two-dimensional (2D) ISAR imaging of rotating parts. Based on this model, the real-valued inverse Radon transform is applied to image formation in the range-slow time domain. Then we put forward a complex-valued inverse Radon transform for imaging of rotating parts, which utilizes both the sinusoidal modulus and the phase of the radar echoes. Additionally, we analyze possible problems when applying these algorithms in real world situations and provide corresponding solutions. Finally, the effectiveness of the algorithms is demonstrated using simulated and measured data. [ABSTRACT FROM AUTHOR]

Although it is difficult to assess the achievable performance of nonlinear tracking applications, it nevertheless remains extremely important to do so. This paper illustrates how the mean and covariance of the estimated online state can be used to recursively calculate an approximate posterior Cramer-Rao lower bound (CRLB). Most CRLB implementations require the true state, but this is impractical except for appropriately designed experiments or simulations where the exact value of the state is given as prior knowledge. The performance of the approximate posterior CRLB (PCRLB) used in conjunction with the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) for online state estimation are investigated. To test the validity of the proposed method, it was applied to the problem of tracking a ballistic object on reentry. Simulation results confirm the theory and reveal that the proposed approximate PCRLB is sufficiently accurate and that the PCRLB approximations obtained using different state filters are in general very close to each other. [ABSTRACT FROM AUTHOR]