Abstracts:An attractive and challenging problem in source localisation is to locate a target in three-dimensional (3D) space using a single station. To satisfy the observability requirements and achieve higher accuracy, the authors draw on the idea of the inverse synthetic aperture radar for single-station localisation, which leverages the mobility of target and a time serial measurements of angle of arrival (AoA) and time difference of arrival (TDoA). A closed-form pseudo-linear estimator (PLE) is developed to estimate both 3D position and velocity of mobile target through the linearisation of AoA–TDoA measurement equations. Furthermore, to suppress the large bias of PLE caused by the correlation of measurement noise, the authors propose a superior bias-reduced estimator (BRE), which imposes a quadratic constraint to minimise the noise correlation term. They prove that BRE is asymptotically efficient, attaining the Cramér-Rao lower bound (CRLB) over the moderate noise region. Extensive simulations show that both bias and mean square error of BRE are well predicted by theoretical analysis. Most importantly, in comparison with both PLE and two traditional bias reduction methods, namely weighted total least squares and weighted instrumental variables, BRE can approach the CRLB over a wider noise region and maintain a lower bias.

Abstracts:The vector tracking structure is receiving growing attention due to its better tracking performance than the traditional scalar tracking structure. For the scalar tracking structure, signal quality monitoring (SQM) methods can effectively detect spoofing attacks based on the influence of correlation peaks overlap on the coherent integration results. However, the methods are invalid when the overlap is inexistent. While for the vector tracking structure, the authors find that because of the combined tracking of all received signals, the coherent integration results are affected by spoofing attacks regardless of whether the overlap exists. It implies that SQM techniques have a wider application range for the vector tracking structure. To this end, an SQM-based spoofing detection method for the vector tracking structure is proposed in this study. Analysis and simulation results demonstrate that the proposed method is useful even in the spoofing scenarios where the correlation peaks do not overlap. And it can detect spoofing attacks on both pseudo-code and carrier Doppler by using the existing observations in the tracking process, which is highly practical for the vector tracking structure.

Abstracts:This study handles the three-dimensional (3D) angle-only tracking (AOT) problem, which is calculating the target's location and velocity by measuring the target's elevation and azimuth angle. Nowadays, a non-civilian (unmanned) aircraft can accelerate in an unpredictable manner. This study presents a stochastic filter re-start strategy for tracking a target which can abruptly change its velocity in any 3D directions. Moreover, this study assumes that the target's destination information is known a priori. Using the target destination information, the authors can improve the filter accuracy as well as the time efficiency. As far as they know, this study is novel in using the target's destination information for manoeuvring target tracking in 3D AOT problem. The performance of the proposed stochastic filter re-start strategy based on the target's destination information is verified under MATLAB simulations.

Abstracts:High-frequency surface-wave radar (HFSWR) is widely used in vessel and aircraft detection, sea-state sensing and wind-field mapping. Target detection suffers from the ionospheric clutter, which is reflected by the ionosphere. Adaptive beamforming (ABF) has been used for ionospheric clutter mitigation. However, the performance of ABF is limited by the heterogeneous ionospheric clutter and degrees of freedom (DOF) of the antennas array. In order to improve the performance, here, the one-dimensional ABF is expanded to two-dimensional fast-time space–time adaptive processing (STAP), which combines beam and range domains to obtain more DOFs than that in the ABF. In addition, the blind sources separation (BSS) method is also used to improve the spatial covariance matrix estimation accuracy of STAP in the heterogeneous ionospheric clutter background. The simulation and real data results demonstrate the effectiveness of the proposed BSS-STAP method in HFSWR.

Abstracts:The frequency diverse array multiple-input multiple-output (FDA-MIMO) radar provides range estimation capability by exploiting a small frequency offset across the transmit sensors, which has been utilised in numerous applications. However, the estimation performance is basically limited by the array geometry and signal bandwidth. In this study, the authors propose a new FDA-MIMO framework, i.e. the unfolded coprime array with ‘unfolded’ coprime frequency offsets (UCA-UCFO) framework, for joint angle and range estimation without ambiguity. The array aperture and signal bandwidth are obviously expanded by employing UCA in the spatial domain and frequency domain, which results in significantly enhanced estimation accuracy and resolution. In addition, we construct the joint angle and range estimation problem as a two-dimensional (2D)-multiple signal classification spatial spectrum and transform 2D total spectrum search into a 1D local spectrum search by introducing a successive iteration (SUIT) algorithm. The SUIT algorithm can significantly relieve the computational burden but without performance degradation. The Cramér–Rao bounds of angle and range are provided as a performance benchmark. The analysis and simulations have validated the superiority and advantages of the UCA-UCFO framework and SUIT algorithm with respect to location accuracy, resolution, and computational complexity.

Abstracts:Magnetron-based marine radar technology is mature, affordable, reliable, and very effective for maritime safety applications. Commercial systems may be procured at a modest cost as compared to fully coherent solid-state systems. Magnetron oscillators inherently generate random phase signals. Phase instability on a pulse-to-pulse basis impedes this class of marine radars from success in applications requiring coherency such as moving target indication (MTI) or in generating target imagery. This limitation may be overcome by incorporating radio frequency sampling and cross-correlation of the transmit and receive signal technology to augment the current capability of available systems. In this research, the pulse train on transmit and receive is correlated in order to reject interference and detect image targets. Sampling the transmit signal and target echo on receive permits fully coherent processing. Marine radars traditionally operate non-coherently, and as such, offer limited surveillance in clutter rich environments. In this study, the authors report on a non-coherent marine radar that has been modified to produce a pseudo-coherent or coherent-on-receive sensor system. This is crucial to MTI and target image formation. In laboratory experiments, they employed a magnetron oscillator-based system to generate an inverse synthetic aperture radar image. The image was formed using four different algorithms: filtered back-projection (FBP), time domain back-projection (TDBP), an algebraic reconstruction technique, and frequency domain back-projection. In their research, TDBP produces exquisite imagery of steel rods, and it is the standard developed in this study. FBP performed poorly as compared to all other algorithms.

Abstracts:To apply the Ramanujan filter bank based on the compressed sensing theory to the period estimation of multiple sets of radar pulses, alternatives to period data and the Ramanujan Subspace are proposed in this study. First, the rationality of alternatives to the TOA (time of arrival) model is illustrated by comparing the advantages and disadvantages of the time-point model and the TOA model. Next, by clarifying the zero-sum energy property of the Ramanujan Subspace, the possibility of finding an alternative to the discrete Fourier transform sequence with smaller data is proved. On this basis, a new algorithm for estimating the stagger period of mixed pulses is proposed, which introduces the initial phase of the stagger pulses. The results of the experiments show that the algorithm can accurately estimate the hidden stagger periods of mixed pulses, and it is adept at dealing with false and missing mixed pulses.

Abstracts:In this paper, a novel prediction-discrepancy based on innovative particle filter (PDIPF) is proposed to solve the unmanned aerial vehicle (UAV) positioning problem in the presence of the global positioning system (GPS) spoofing attack, supposing that the GPS spoofing effects are in the form of unknown but bounded errors. To cope with the GPS spoofing attacks as unknown sudden changes of system state variables, the compensation of the GPS spoofing effects is adaptively done in two basic parts of PDIPF algorithm including particle weighting and covariance matrix adaption. In addition, a theorem is developed which verifies that the output estimation error is upper bounded by a given probability with the help of the adapted covariance matrix. Besides, the particle weight calculation in PDIPF is done with respect to the prediction discrepancy of generated particles from the GPS measurements. The proposed PDIPF is used to decrease the effects of any GPS spoofing errors with different probability density functions and estimate true position of UAV in the presence of the GPS spoofing attacks. The algorithm is applied to the inertial navigation system/GPS/Loran-C integration systems. Simulation results demonstrate the effectiveness of the proposed PDIPF algorithm in terms of accuracy and redundancy.

Abstracts:In this study, by employing the intra-pulse cross-correlation (IPCC) operation, an unambiguous velocity estimation method is proposed for narrow-band long-range radars with high carrier frequency and low pulse repetition frequency. This estimation algorithm is simple and could be easily implemented in existing radar systems without changing the radar hardware or the pulse transmitting scheme. Comparing with the slow time dimension correlation algorithm, the accuracy of the proposed intra-pulse frequency domain method is greatly improved, and the brute-force search for the unknown motion parameters is also unnecessary. By first setting a small frequency offset of the IPCC operation, the unambiguous velocity region could be significantly enlarged. Using the relatively coarse but unambiguous estimates and increasing the frequency offset step by step, the IPCC is repeatedly applied to obtain more accurate estimates. Note that the estimation results of the IPCC algorithm could be used in the maximum-likelihood estimator for ambiguity resolution. The Cramér-Rao bound for the proposed algorithm is derived, and the optimal frequency offset in the sense of estimation accuracy is also analysed. Through numerical simulations for both synthetic and real radar data, the effectiveness of the proposed estimation algorithm is verified.

Abstracts:BPSK is the basis of current GNSS (Global Navigation Satellite System) signals. BDS (Beidou navigation satellite system) RDSS (Radio Determination Satellite Service) system also adopts BPSK to realize communication and ranging simultaneously. To realize higher system capacity, RDSS signals overlap in time and frequency domain. The signal performance is heavily determined by the MAI (Multiple Access Interference) between overlapping signals. In this paper, SSMSK (spread spectrum MSK) is proposed. The signal performance is investigated under four conditions considering the main lobe bandwidth and the receiver bandwidth. The maximum number of overlapping signals for SSMSK is 11.7% higher than BPSK when the receiver bandwidth is for the side subcarrier. And the value is 10.6% when the receiver bandwidth is. SSMSK can be received utilizing BPSK local signal. When the receiving bandwidth is <inline-formula><alternatives><tex-math notation="TeX">$2R_c$</tex-math><mml:math overflow="scroll"><mml:mn>2</mml:mn><mml:msub><mml:mi>R</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:math><inline-graphic xlink:href="IET-RSN.2019.0533.IM4.gif" /></alternatives></inline-formula>, the correlation peak of SSMSK_BPSK is identical to BPSK. The tracking accuracy of SSMSK is higher than BPSK when the correlation interval is between 0.2-1 chips. The accuracy of SSMSK_BPSK is higher than BPSK when the correlation interval is 0.5 chips. The disadvantage of SSMSK is larger quantization word length. SSMSK is a better modulation for RDSS based on the comprehensive performance.