Xing-Peng Mao

A multi-domain collaborative filter for HFSWR based on oblique projection

Radio frequency interference (RFI) cancellation is a main problem to be solved in High Frequency Surface Wave Radar (HFSWR) system. To minimize the impact of RFI, a number of signal processing techniques, such as adaptive beamforming and polarization filtering, have been developed. However, the performance of these conventional methods degrades a lot when the target and interferences have similar parameters within the corresponding processing domains. According to the fact that target usually differs with RFI in more than one domain, it will be beneficial to suppress interferences by constructing a joint filter that includes multiple domains like frequency, space and polarization, etc. In this paper, a multi-domain collaborative filer (MDCF) based on oblique projection is proposed. The construction of oblique projection spatial-frequency-polarization filter (OPSFPF), oblique projection spatial-polarization filter (OPSPF) and oblique projection spatial filter (OPSF) is introduced. Theoretical analysis and simulation results demonstrate that the multi-domain collaborative filter is feasible and performs better when more processing domains are included. Such filter could take full advantage of the differences between the target and interference and, consequently improves the effect of RFI suppression in HFSWR.

Research on Polarization Cancellation of Nonstationary Ionosphere Clutter in HF Radar System

Oblique projection polarization filter (OPPF) can be applied as an effective approach for interference cancellation in high-frequency surface wave radar (HFSWR) and other systems. In order to suppress the nonstationary ionosphere clutter further, a novel OPPF based clutter suppressing scheme is proposed in this paper. The polarization and nonstationary characteristic of the clutter are taken into account in the algorithms referred to as range-Doppler domain polarization suppression (RDDPS) and the range-time domain polarization suppression (RTDPS) method, respectively. The RDDPS is designed for weak ionosphere clutter and implemented in the range-Doppler domain directly, whereas the RTDPS algorithm is designed to suppress the powerful ionosphere clutter with a multisegment estimation and suppression scheme. About 15–23 dB signal to interference ratio (SIR) improvement can be excepted when using the proposed method, whereas the targets can be more easily detected in the range-Doppler map. Experimental results demonstrate that the scheme proposed is effective for nonstationary ionosphere clutter and is proven to be a practical interference cancellation technique for HFSWR.

Narrow-band null phase-shift spatial filter based On oblique projection

Normal methods of spatial filtering methods may change the coherent characteristic of the target, which reduces the effect of accumulation in coherent systems despite the improvement of signal-to-interference and noise ratio (SINR). To avoid the amplitude and phase distortion introduced by the filters, null phase-shift spatial filter (NPSF) is proposed in this paper. NPSF can suppress the interference while keeping the original information of the target signal. However, the performance of NPSF will be influenced by the estimation error of the targets spatial parameter. To solve this problem, an improved NPSF, narrow-band null phase-shift spatial filter (NNPSF), is proposed. The method to construct the weight vector of NNPSF is introduced. Theoretical analysis and simulation results demonstrate that the NNPSF is a valid spatial filtering technology. With reducing the accuracy of estimation, NNPSF is more suitable and robust in practical systems.

Multi-domain collaborative filter for interference suppressing

Filters with antenna arrays are widely used for interference suppression in the temporal domain, frequency domain, space domain and so on. Meanwhile, the interference mitigation performance of a single-domain-based filter depends on a noticeable difference between the target signal and interference in the corresponding domain. However, the interference cannot be efficiently suppressed by a single-domain-based filter when the difference in this individual domain is small. To solve this problem, a multi-domain collaborative oblique projection filter is proposed in this study. First, multi-domain spaces are theoretically derived to distinguish the target signal and the interference, and then a multi-domain oblique projection operator is provided to recover the original target and suppress the interference. Depending on the multi-domain spaces, the filter has excellent performance when the difference is insignificant in each individual domain, whereas the performances of the single-domain-based filter and cascade filter degrade significantly. Finally, a space–polarisation–frequency domain collaborative filter based on oblique projection is given as an illustration. Performance analysis and simulation results are provided to illustrate the superiority of the proposed filter for interference mitigation.

An oblique projection filtering based DOA estimation algorithm without a priori knowledge

The high resolution multiple signal classification (MUSIC) algorithm provides an efficient way to estimate direction- of-arrival (DOA). However, it performs poorly when weak signals are accompanied with strong ones. To solve this problem, an oblique projection filtering based DOA estimation algorithm is proposed without using a priori knowledge of the sources, such as directions, strength, modulation modes, etc. Numerical results verify the effectiveness of the proposed algorithm. It is shown that a high resolution DOA estimation of the incident sources can be achieved. The detection performances for weak signals are more stable and superior than that of the MUSIC algorithm.

A generalized oblique projection operator for interference suppression under colored noise

The existing oblique projection (OP) technique usually pays attention to white background noise, but a colored noise assumption is more practical. To solve this problem, a minimized interference constrained generalized oblique projection (MIGOP) operator is proposed under colored noise scenario for interference suppression. It is proven that the OP filter is a special case of the MIGOP filter whereas the latter is more suitable to suppress interference under colored noise scenario. The traditional linearly constrained minimum variance (LCMV) filter and the MIGOP filter are two special cases of the generalized oblique projection (GOP) filters. An LCMV filter can be used to obtain the maximal signal to interference plus noise ratio (SINR), whereas an MIGOP filter can be used to obtain both the maximal SINR and the signal to interference ratio (SIR). The performance comparison among the MIGOP filter, the OP filter and the traditional LCMV filter are illustrated. Conclusions are made based on analysis and simulations.

An infinity-norm based flexible semidefinite programming technique for elliptical localization

This paper focuses on elliptical localization for a multi-static passive radar, when an uncooperative transmitter is considered. We take two factors into account: the error in transmitter position and the range-dependent measurement noise. When no prior is provided on the errors bound or variance, it is found that most existing algorithms become invalid. Following this and based on the infinity-norm optimization criterion, a min-max flexible semidefinite programming (MMF-SDP) technique is developed to achieve novel estimation results. MMF-SDP works by decomposing the noise components into independent ones and then treating them as optimization parameters. Relationship between the noise components on different measurements is also explored, which helps guarantee a rank-one semidefinite relaxation. Numerical results collaborate with our theory and the superiority of MMF-SDP is also illustrated.

Design methods for ULA-based directional antenna arrays by shaping the Cramér–Rao bound functions

This study focuses on the design methods for uniform linear array (ULA) based directional antenna arrays by optimising the radiation characteristics of elements. To improve the performance of direction-of-arrival (DOA) estimation in a predetermined objective spatial sector which includes all the potential directions of incidence, Cramer–Rao bound based optimisation models are established by utilising the least squares fitting technique. Besides, a modified simulated annealing (SA) algorithm with the iteration of parameters is proposed, aiming to solve the optimisation problems when the classic SA is invalid. Compared with the corresponding conventional ULA, an optimised array can obtain higher accuracy of DOA estimation in the objective spatial sector with little fluctuation. Additionally, the optimised design of radiation characteristics can also suppress the ambiguities, and remains effective for the arrays with different aperture. Simulation results verify the effectiveness of the proposed methods and the superiority of the optimised arrays.

Oblique projection for direction-of-arrival estimation of hybrid completely polarised and partially polarised signals with arbitrary polarimetric array configuration

This study deals with the direction-of-arrival (DOA) estimation problem for hybrid completely polarised (CP) and partially polarised (PP) source signals using arbitrary polarimetric antenna arrays. An oblique projection-based polarisation insensitive direction estimation (OPPIDE) algorithm is proposed by exploiting the spatial-sparsity property of the sources. The OP technique is utilised to provide spatial filters, which are insensitive to the state of polarisation of signals, so that the potential source signals in the spatial domain can be separated later. The DOA estimation is finally implemented by identifying the sources’ spatially sparse structure with the separated signals. Theoretical analysis indicates that the OPPIDE is applicable to any hybrid CP and PP signals, and is independent of special polarimetric array configurations. The effectiveness and superiority of the proposed OPPIDE are substantiated through making performance comparison with the present counterpart algorithms.

Reducing errors for root-MUSIC-based methods in uniform circular arrays

Root-MUSIC can be applied to uniform circular array (UCA) to achieve computationally efficient direction of arrival (DOA) estimation via beamspace transformation (BT). When the number of sensors of a UCA is small, the residual errors introduced by the BT will have significant values, resulting in performance degradation for DOA estimation. To solve this problem, an algorithm that enables the modification of the beamspace sample covariance matrix (BSCM) by considering the residual components is proposed. First, the residual components in the BSCM are calculated based on the initial DOAs estimated by the UCA root-MUSIC-based methods. Then the BSCM is modified by removing the undesirable terms. Finally, better DOA estimation performance is obtained by using the revised BSCM. The computational complexity and estimation error are derived. The significant advantages of the proposed algorithm are demonstrated by the simulation results.