Feng Shen

Robust Beamforming with Magnitude Response Constraints and Conjugate Symmetric Constraint

In this letter, a novel robust adaptive beamformer is proposed with magnitude response constraints and conjugate symmetric constraint. With the constraints on magnitude response, we can flexibly control the robust response region with specified beamwidth and response ripple. However, due to the non-convex lower bound magnitude response constraint, conventional convex optimization techniques cannot be applied directly. To overcome this, we exploit the symmetric structure of the array weights to transform the non-convex constraint into a convex one without any relaxation or approximation. In order to obtain a more robust beamformer against all kinds of array imperfections, we further extend the proposed approach to deal with the optimization of worst-case performance.

Robust Adaptive Beamforming Based on Steering Vector Estimation and Covariance Matrix Reconstruction

In this letter, a novel robust adaptive beamforming (RAB) technique is proposed. It offers robust performance even with large look direction error in the array steering vector (ASV) and an uncertainty in the covariance matrix. In essence, the proposed ASV estimation technique treats the ASV as a vector lying within the intersection of two subspaces, and then estimates it using a closed-form formula. In this technique, the covariance matrix is reconstructed after the desired signal (DS) eigenvalue is replaced by the average value of the noise eigenvalues, thus eliminating a large portion of the DS. Furthermore, the only prior information necessary is knowledge of the antenna array geometry and angular sector in which the actual ASV lies. Simulation results indicate that the proposed method achieves good performance in terms of output signal-to-interference-plus-noise ratio (SINR), as long as the input signal-to-noise ratio (SNR) is not close to the interference-to-noise ratio (INR) and the DS and interference signals are well separated.

Unambiguous Acquisition Technique for Cosine-Phased Binary Offset Carrier Signal

In this letter, an unambiguous acquisition technique is proposed for cosine-phased binary offset carrier (BOC) modulated signals. The test criterion used in this technique is based on a synthesized correlation function that has no positive side peak. This synthesized correlation function is obtained from the difference of two squared cross-correlation functions of the received cosine-BOC (m,n) signal with two local auxiliary signals. The modulated symbols of the local auxiliary signals are derived and simulations show that the proposed method completely removes the ambiguity threat in acquisition process at a cost of minor degradation in the detection probability and the complexity of the proposed method is reduced significantly. The proposed technique is also suitable for arbitrary order cosine-BOC signals.

A novel method of multipath mitigation for C/A code tracking loop based on wavelet transform

Multipath is one of main errors in GPS and other spread spectrum systems, it seriously affects the performance of the navigation receiver. In this paper the correlation model under multipath signal is analyzed and we analyze the characteristics of the autocorrelation function starting with it, then a method of detecting jumping-off point of autocorrelation function based on wavelet analysis is proposed, further more, the discriminator result is got to adjust the C/A phase in DLL. Theory analysis and simulation results show that the method is not restricted by the numbers of multipath and sky-wave interference, and better multipath mitigating performance can be acquired than narrow correlation.

Parameter estimation of alpha-stable distributions based on MCMC

The α -stable distribution is a very flexible tool to model NonGaussian data. Stable distributions can allow for modeling infinite variance, skewness and heavy tails, but gives rise to inferential problems related to the estimation of the stable distribution parameters. In this work, we study the estimation of α -stable distributions using numerical Bayesian sampling techniques such as Markov chain Monte Carlo (MCMC), which can simultaneously estimate the four parameters of the model with good performance. Metropolis-Hastings algorithm is used to update the parameters of α -stable distribution at every iteration. The simulation results show that our estimation method is capable of estimating all the parameters accurately.

A weak target detection method for GPS based passive radar

In this paper the problem of disturbance cancellation in the surveillance channel of passive radar system, which exploits GPS transmitter as the illuminator, is addressed. The presence of direct-path interference (DPI) and multi-path interference (MPI) strongly affect the detection performance of passive radar. In the receiver system, the echo reflected from the target would be buried under the DPI and MPI. To solve this problem, the LS-CLEAN algorithm based on the lease-square method and CLEAN algorithm is proposed to suppress the interference. The DPI and MPI are removed iteratively by projecting received signals into the subspace which is orthogonal to the disturbance subspace. The effectiveness of the algorithm is demonstrated by simulation results.

New detection algorithm for weak target signal embedded in direct path interference using Signal Phase Matching Principle

A detection method for weak signals embedded in direct-path interference is discussed. This method is based on FM radio signals as the illuminator of passive radar. On the basic of Signal Phase Matching Principle, a new algorithm for suppressing the direct-path interference is proposed in wave-beam domain. To improve the declining performances of the algorithm when the amplitude fluctuates, a compensatory factor is presented. The simulation results show the validity of the algorithm and the compensatory method.

PN code acquisition using locally optimum statistics in blind channels

For the conventional pseudonoise (PN) code acquisition systems in blind channels, both full knowledge of the joint In-phase and Quadra-phase (I and Q) noise density is required. In order to reduce the computational complexity, a new PN code acquisition detector is proposed for direct sequence spread spectrum systems in blind channels based on locally optimal (LO) detector. This detector can efficiently reduce the computational complexity of locally optimum detector. Numerical results show that the proposed detector can work well without the prior-information about the channels and offer substantial performance improvement over the conventional square-sum (SS) detector in blind channels.