Range-Angle-Dependent Beamforming by Frequency Diverse Array Antenna

This paper proposes a range-angle-dependent beamforming for frequency diverse array (FDA) antenna systems. Unlike conventional phased-array antenna, the FDA antenna employs a small amount of frequency increment compared to the carrier frequency across the array elements. The use of frequency increment generates an antenna pattern that is a function of range, time and angle. The range-angle-dependent beamforming allows the FDA antenna to transmit energy over a desired range or angle. This provides a potential to suppress range-dependent clutter and interference which is not accessible for conventional phased-array systems. In this paper, a FDA radar signal model is formed and the range-angle-dependent beamforming performance is examined by analyzing the transmit/receive beampatterns and the output signal-to-interference-plus-noise ratio (SINR) performance. Extensive simulation examples and results are provided

An Improved SNR Estimator for Wireless OFDM Systems

AbstractSNR is a crucial parameter for OFDM system and the assistant technology thereof such as Turbo coding, channel equalization. In this paper, we propose an improved SNR estimator which can be applied for the pilot structure in 3GPP standard. The modified second order moments of the pilot points after FFT are used to estimate noise variance in OFDM packets. The channel frequency responses of four subcarriers from adjacent two pilot points in distinct symbols could be used to inhibit the channel fading. Simulation results show that the proposed algorithm is robust to frequency selectivity and time selectivity in wireless channels, and its performance is considerably improved compared with the available methods

Performance Prediction of a Synchronization Link for Distributed Aerospace Wireless Systems

For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link

Frequency Diverse Array MIMO Radar Adaptive Beamforming with Range-Dependent Interference Suppression in Target Localization

Conventional multiple-input and multiple-output (MIMO) radar is a flexible technique which enjoys the advantages of phased-array radar without sacrificing its main advantages. However, due to its range-independent directivity, MIMO radar cannot mitigate nondesirable range-dependent interferences. In this paper, we propose a range-dependent interference suppression approach via frequency diverse array (FDA) MIMO radar, which offers a beamforming-based solution to suppress range-dependent interferences and thus yields much better DOA estimation performance than conventional MIMO radar. More importantly, the interferences located at the same angle but different ranges can be effectively suppressed by the range-dependent beamforming, which cannot be achieved by conventional MIMO radar. The beamforming performance as compared to conventional MIMO radar is examined by analyzing the signal-to-interference-plus-noise ratio (SINR). The Cramér-Rao lower bound (CRLB) is also derived. Numerical results show that the proposed method can efficiently suppress range-dependent interferences and identify range-dependent targets. It is particularly useful in suppressing the undesired strong interferences with equal angle of the desired targets

Joint Phased-MIMO and Nested-Array Beamforming for Increased Degrees-of-Freedom

Phased-multiple-input multiple-output (phased-MIMO) enjoys the advantages of MIMO virtual array and phased-array directional gain, but it gets the directional gain at a cost of reduced degrees-of-freedom (DOFs). To compensate the DOF loss, this paper proposes a joint phased-array and nested-array beamforming based on the difference coarray processing and spatial smoothing. The essence is to use a nested-array in the receiver and then fully exploit the second order statistic of the received data. In doing so, the array system offers more DOFs which means more sources can be resolved. The direction-of-arrival (DOA) estimation performance of the proposed method is evaluated by examining the root-mean-square error. Simulation results show the proposed method has significant superiorities to the existing phased-MIMO

Azimuth-Variant Signal Processing in High-Altitude Platform Passive SAR with Spaceborne/Airborne Transmitter

Abstract: High-altitude platforms (HAP) or near-space vehicle offers several advantages over current low earth orbit (LEO) satellite and airplane, because HAP is not constrained by orbital mechanics and fuel consumption. These advantages provide potential for some specific remote sensing applications that require persistent monitoring or fast-revisiting frequency. This paper investigates the azimuth-variant signal processing in HAP-borne bistatic synthetic aperture radar (BiSAR) with spaceborne or airborne transmitter for high-resolution remote sensing. The system configuration, azimuth-variant Doppler characteristics and two-dimensional echo spectrum are analyzed. Conceptual system simulation results are also provided. Since the azimuth-variant BiSAR geometry brings a challenge for developing high precision data processing algorithms, we propose an image formation algorithm using equivalent velocity and nonlinear chirp scaling (NCS) to address the azimuth-variant signal processing problem. The proposed algorithm is verified by numerical simulation results

A Nyström-Based Low-Complexity Algorithm with Improved Effective Array Aperture for Coherent DOA Estimation in Monostatic MIMO Radar

In this paper, we propose a computationally efficient algorithm with improved effective aperture for coherent angle estimation in a monostatic multiple-input multiple-output (MIMO) radar. First, the direction matrix of MIMO radar is mapped into a low-dimensional matrix of virtual uniform linear array (ULA). Then, an augmented data expansion matrix with improved effective aperture is obtained by exploiting the Vandermonde-like structure of the low-dimensional direction matrix and radar cross section (RCS) matrix to enlarge the aperture of the array. Next, a unitary transformation is used to transform the augmented matrix into a real value and the approximate signal subspace of the augmented matrix is obtained by the Nyström method, which can reduce the computational complexity. The eigenvectors of the approximate signal subspace are used to reconstruct the matrix for direct decorrelation processing. Finally, direction of arrivals (DOAs) can be estimated faster by utilizing the unitary ESPRIT algorithm since the rotation invariance of the extended reconstruction matrix still exists. The proposed algorithm has a lower total computational complexity, and the estimation accuracy is improved by utilizing real values and enlarging the array aperture for estimation. Several theoretical analyses and simulation results confirm the effectiveness and advantages of the proposed method

Radar-to-Radar Interference Suppression for Distributed Radar Sensor Networks

Radar sensor networks, including bi- and multi-static radars, provide several operational advantages, like reduced vulnerability, good system flexibility and an increased radar cross-section. However, radar-to-radar interference suppression is a major problem in distributed radar sensor networks. In this paper, we present a cross-matched filtering-based radar-to-radar interference suppression algorithm. This algorithm first uses an iterative filtering algorithm to suppress the radar-to-radar interferences and, then, separately matched filtering for each radar. Besides the detailed algorithm derivation, extensive numerical simulation examples are performed with the down-chirp and up-chirp waveforms, partially overlapped or inverse chirp rate linearly frequency modulation (LFM) waveforms and orthogonal frequency division multiplexing (ODFM) chirp diverse waveforms. The effectiveness of the algorithm is verified by the simulation results

A Nyström-Based Low-Complexity Algorithm with Improved Effective Array Aperture for Coherent DOA Estimation in Monostatic MIMO Radar

In this paper, we propose a computationally efficient algorithm with improved effective aperture for coherent angle estimation in a monostatic multiple-input multiple-output (MIMO) radar. First, the direction matrix of MIMO radar is mapped into a low-dimensional matrix of virtual uniform linear array (ULA). Then, an augmented data expansion matrix with improved effective aperture is obtained by exploiting the Vandermonde-like structure of the low-dimensional direction matrix and radar cross section (RCS) matrix to enlarge the aperture of the array. Next, a unitary transformation is used to transform the augmented matrix into a real value and the approximate signal subspace of the augmented matrix is obtained by the Nyström method, which can reduce the computational complexity. The eigenvectors of the approximate signal subspace are used to reconstruct the matrix for direct decorrelation processing. Finally, direction of arrivals (DOAs) can be estimated faster by utilizing the unitary ESPRIT algorithm since the rotation invariance of the extended reconstruction matrix still exists. The proposed algorithm has a lower total computational complexity, and the estimation accuracy is improved by utilizing real values and enlarging the array aperture for estimation. Several theoretical analyses and simulation results confirm the effectiveness and advantages of the proposed method