A new method for resolving phase ambiguity in radio interferometry using Earth rotation synthesis

As a key technique in deep space navigation, radio interferometry can be used to determine the accurate location of a spacecraft in the plane-of-sky by measuring its signal propagation time delay between two remote stations. To improve the measurement accuracy, differential phase delay without phase ambiguity is usually desired. Aiming at the difficulties of resolving phase ambiguity with few stations and narrowband downlink signals, a new method is proposed in this work by taking advantage of the Earth rotation. The high accurate differential phase delay between the spacecraft and a calibrator can be achieved not only in the in-beam observation mode but also in the out-of-beam observation mode. In this paper we firstly built the model of phase ambiguity resolution. Then, main measurement errors of the model are analyzed, which is followed by tests and validations of the model and method using the tracking data of the Cassini mission and Chang'E-3 mission. The results show that the phase ambiguities can be correctly resolved to generate a 10-picosecond level accuracy differential phase delay. Angular measurement accuracy of the Cassini reaches the milli-arc-second level, and the relative position accuracy between the Chang'E-3 rover and lander reaches the meter level.

Research on the method of dual-frequency microwave diagnosis of plasma for solving phase integer ambiguity

In this work,microwaves and terahertz waves have performed a dual-frequency combineddiagnosis in high-temperature,large-scale plasma.According to the attenuation and phase shift of electromagnetic waves in the plasma,the electron density and collision frequency of theplasma can be inversely calculated.However,when the plasma size is large and the electron density is high,the phase shift of the electromagnetic wave is large(multiple times 2πperiod).Due to the limitations of the test equipment,the true phase shift is difficult to test accurately or to recover reality.That is,there is a problem of phase integer ambiguity.In order to obtain a phase shift of less than 180°,a higher electromagnetic wave frequency(terahertz wave with 890 GHz)is used for diagnosis.However,the attenuation of the terahertz wave diagnosis is too small(less than 0.1 d B),only the electron density can be obtained,and the collision frequency cannot be accurately obtained.Therefore,a combined diagnosis was carried out by combining twofrequencies(microwave with 36 GHz,terahertz wave with 890 GHz)to obtain electron density and collision frequency.The diagnosis result shows that the electron density is in the range of(0.65–1.5)×1019m^(-3),the collision frequency is in the range of 0.65–2 GHz,and the diagnostic accuracy is about 60%.

Low-complexity fractional phase estimation for totally blind channel estimation

To remove the scalar ambiguity in conventional blind channel estimation algorithms, totally blind channel estimation （TBCE） is proposed by using multiple constellations. To estimate the unknown scalar, its phase is decomposed into a fractional phase and an integer phase. However, the maximum-likelihood （ML） algorithm for the fractional phase does not have closed-form solutions and suffers from high computational complexity. By ex- ploring the structures of widely used constellations, this paper proposes a low-complexity fractional phase estimation algorithm which requires no exhaustive search. Analytical expressions of the asymptotic mean squared error （MSE） are also derived. The theo- retical analysis and simulation results indicate that the proposed fractional phase estimation algorithm exhibits almost the same performance as the ML algorithm but with significantly reduced computational burden.

Monopulse instantaneous 3D imaging for wideband radar system

To avoid the complicated motion compensation in interferometric inverse synthetic aperture(InISAR)and achieve realtime three-dimensional(3 D)imaging,a novel approach for 3 D imaging of the target only using a single echo is presented.This method is based on an isolated scatterer model assumption,thus the scatterers in the beam can be extracted individually.The radial range of each scatterer is estimated by the maximal likelihood estimation.Then,the horizontal and vertical wave path difference is derived by using the phase comparison technology for each scatterer,respectively.Finally,by utilizing the relationship among the 3 D coordinates,the radial range,the horizontal and vertical wave path difference,the 3 D image of the target can be reconstructed.The reconstructed image is free from the limitation in InISAR that the image plane depends on the target's own motions and on its relative position with respect to the radar.Furthermore,a phase ambiguity resolution method is adopted to ensure the success of the 3 D imaging when phase ambiguity occurs.It can be noted that the proposed phase ambiguity resolution method only uses one antenna pair and does not require a priori knowledge,whereas the existing phase ambiguity methods may require two or more antenna pairs or a priori knowledge for phase unwarping.To evaluate the performance of the proposed method,the theoretical analyses on estimation accuracy are presented and the simulations in various scenarios are also carried out.

Fixed-point ICA algorithm for blind separation of complex mixtures containing both circular and noncircular sources

Fixed-point algorithms are widely used for independent component analysis（ICA） owing to its good convergence. However, most existing complex fixed-point ICA algorithms are limited to the case of circular sources and result in phase ambiguity, that restrict the practical applications of ICA. To solve these problems, this paper proposes a two-stage fixed-point ICA（TS-FPICA） algorithm which considers complex signal model. In this algorithm, the complex signal model is converted into a new real signal model by utilizing the circular coefficients contained in the pseudo-covariance matrix. The algorithm is thus valid to noncircular sources. Moreover, the ICA problem under the new model is formulated as a constrained optimization problem, and the real fixed-point iteration is employed to solve it. In this way, the phase ambiguity resulted by the complex ICA is avoided. The computational complexity and convergence property of TS-FPICA are both analyzed theoretically. Simulation results show that the proposed algorithm has better separation performance and without phase ambiguity in separated signals compared with other algorithms. TS-FPICA convergences nearly fast as the other fixed-point algorithms, but far faster than the joint diagonalization method, e.g. joint approximate diagonalization of eigenmatrices（JADE）.