A new reduced‐rank (RR) space‐time adaptive processing (STAP) algorithm based on multistage selections of angle‐Doppler filters is proposed in the form of a generalised sidelobe canceller. First, two ...types of the RR auxiliary angle‐Doppler filters are designed based on the discrete Fourier basis functions. Then, a novel multistage method is implemented to select the angle‐Doppler filters by using the cross‐correlation observed at the current stage and the residual output observed at the previous stage. Finally, the asymptotic statistic performance of target detection is evaluated in terms of the conventional framework of STAP for the cases of both known and unknown covariance, which shows that the proposed algorithm is capable of providing the constant false alarm rate. Numerical examples are provided, and they demonstrate that the proposed algorithm is able to offer better performance than the existing sparsity‐based and the conventional reduced‐dimension algorithms under the intrinsic clutter motion and array gain and phase errors.
The design of an integrated sensing and communication (ISAC) waveform compatible with the 5G new radio (NR) system is crucial in enabling ISAC by utilizing the hardware of existing base stations ...(BSs). In this paper, we design an inner-frame time division multiplexed sensing waveform in the frame structure of 5G NR to achieve ISAC. The designed waveform is computed by the simulated annealing algorithm on an optimization cost function of a constrained combination of the peak-to-sidelobe ratio (PSLR) and the integrated sidelobe ratio (ISLR) of the velocity ambiguity function. Specifically, the constraints are the 5G communication protocol and 5G NR frame structure. In addition, we conducted corresponding signal detection and estimation methods to illustrate the performance of the sensing waveform. Both theoretical analysis and simulation experiments show that the designed waveform can effectively achieve target detection and parameter estimation under low sensing cost conditions.
With the development of 5G communication systems, it is a hot topic to embed integrated sensing and communication (ISAC) based on the existing 5G base station by sharing the hardware and the same ...frequency spectrum. In this paper, we propose a dual pulse repeated frequency (dual-PRF) waveform design of time-division ISAC (TD-ISAC) based on a 5G new radio (NR) communication system using downlink communication slots. We choose time-division mode to design waveform to avoid the interference between sensing and communication. Embedding sensing functions in a 5G NR system, we design a dual-PRF sensing slot to satisfy the constraints of common channel and uplink communication. Considering two uplink modes, namely flexible and fixed, we design two dual-PRF waveforms and illustrate the sensing theory performance of the designed waveform by the ambiguity function. Then, we exploit the designed waveform to the vehicle parameter estimation. To verify that the designed waveform has good adaptability to different signal processing methods, we realize the parameter estimation by two types of methods: the discrete Fourier transformation-based method and the compressed sensing-based method. At last, we verify the effectiveness of the designed waveform system by simulation experiments and real traffic scenarios.
To have a further understanding of the recently developed space-time adaptive processing (STAP) methods based on sparse representation (SR-STAP), this letter details the clutter sparsity observed by ...STAP radar systems. First, we review the principle and discuss the existing problems about clutter sparsity of the SR-STAP-type algorithms. Then, a theoretical analysis on clutter sparsity for a side-looking uniform linear array with constant pulse repetition frequency, constant velocity, and no crab is performed. Some important conclusions are obtained, and simulations are used to validate the correctness of them.
We present a novel sparsity-based space-time adaptive processing (STAP) technique based on the alternating direction method to overcome the severe performance degradation caused by array gain/phase ...(GP) errors. The proposed algorithm reformulates the STAP problem as a joint optimization problem of the spatio-Doppler profile and GP errors in both single and multiple snapshots, and introduces a target detector using the reconstructed spatio-Doppler profiles. Simulations are conducted to illustrate the benefits of the proposed algorithm.
The SAGD start-up process normally circulates steam in both the injector and producer, which consumes a large amount of steam, requires the high cost of high-temperature-produced liquid treatment, ...and unavoidably results in preferential communication in heterogeneous reservoirs. In order to achieve uniform preheat and full steam chamber development in SAGD wellpairs, downhole electrical heating to start up SAGD was proposed and investigated in this study using physical and numerical simulation approaches. Two 3-D scaled physical experiments were designed and implemented to investigate the feasibility and heating characteristics of such a method. Numerical simulation was conducted using an SAGD sector model with typical field properties to design the preheating process, optimize key operational parameters, and formulate the soak strategy to determine the SAGD conversion timing. The experimental results indicate that electrical heating outperforms steam circulation in achieving the uniform thermal communication in heterogeneous reservoirs, which is challenged in the conventional steam circulation process. The preheating process and operational parameters of electrical heating were formulated and optimized, which include wellbore pre-flush, wellbore saturation by heat conduction fluid, electrical heating, and replacement of heat conduction fluid periodically. Surveillance of temperature difference along the horizontal section while powering off electrical heating intermittently is optimized to be the SAGD conversion timing determination strategy. Based on the combination results of scaled physical simulation and pilot wellpair numerical simulation, full heat communication and steam chamber development are achieved along the horizontal length by electrical preheating, and the oil recovery factor of the pilot wellpair is enhanced by 14.8%, indicating encouraging potentials in heavy oil and bitumen development.
Space‐time adaptive processing (STAP) for sparse arrays such as coprime and nested arrays is shown to have improved performance for clutter suppression in airborne radar as compared with uniform ...linear arrays with the same size. However, most of the existing STAP algorithms are derived based on the assumption that the array manifold is exactly known. In this study, a robust STAP algorithm for the clutter suppression with coprime arrays in the presence of gain and phase (GP) errors is proposed. In particular, the virtual space‐time signal with GP errors is first formulated using the covariance matrix of the perturbed array received data under the Gaussian distributed interference assumption. Then, the problem of the clutter spectrum and GP errors' estimates is formulated as a joint minimization optimization problem by exploiting the sparsity of the clutter in the angle–Doppler plane. Finally, a two‐step approach based on the sparse recovery and least‐squared method is developed to solve the resultant optimization problem and the STAP filter can be designed using the clutter spectrum and GP errors' estimates. Compared with the existing sparsity‐based STAP algorithms for coprime arrays, the proposed algorithm shows more robustness to GP errors as illustrated by simulation results.
In this paper, we consider the problem of distributed target detection with subspace signal mismatch. Precisely, the echoes reflected by the distributed target all come from the same direction, and ...the signal steering vector is assumed to lie in a preassigned subspace. However, the actual signal steering vector does not completely belong to the presumed subspace, resulting in subspace signal mismatch. We focus on the design of selective detectors, which have good capabilities of mismatched signal rejection. To this end, we add a fictitious signal under the null hypothesis, which is orthogonal to the nominal signal subspace in the whitened or quasi-whitened subspace. According to the generalized likelihood ratio test criterion, we devise two effective detectors. Compared with the existing ones, the proposed detectors exhibit improved selectivity capabilities for signal mismatch at the price of a little bit performance loss in the case of no signal mismatch. Moreover, for the case of point-like target, which is a special case of distributed target, we derive analytical expressions for the probabilities of detection and false alarm. Simulation results illustrate the superiority of the proposed detectors and confirm our theoretical results.
In this paper, we propose a novel people counting algorithm exploiting convolutional neural network (CNN) using a low radiation impulse radio ultra-wide bandwidth (IR-UWB) radar. Because of the ...ever-changing signals caused by the various cases of human motion scales, superposition and obstruction of signals as well as the attenuate of signal's strength along the distance and the angle, it is not easy to handle the people counting task by directly detecting targets for each range bin. Thus, we hope to excavate the information of targets' patterns, including their densities and forms of patterns' distributions in the detecting region to execute the counting task. To achieve this, the multi-scale range-time maps are extracted from the received data and further used to classify the number of people using the CNN. Finally, the experiments are conducted to show the priority of the proposed algorithm.
In this Letter, the author proposes a novel space–time adaptive processing (STAP) algorithm by enforcing sparse constraint on the beam-Doppler patterns for clutter mitigation when the number of ...training data is limited. By exploiting the sparsity of the beam-Doppler patterns of the STAP filter, the proposed algorithm formulates the filter design as a mixed l2-norm and l1-norm minimisation problem. Moreover, the proposed algorithm develops an adaptive approach to update the regularisation parameter. Simulation results illustrate that the proposed algorithm outperforms the traditional STAP algorithms in a limited sample support.
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