Performance analysis of synchronization errors on digital adaptive beamforming for a high bit-rate QAM receiver

Future defence radar systems, and in particular the ballistic missile defence (BMD) application, demand radar with high resolution in both angle and range. The high resolution angle estimation requires a large antenna aperture of many wavelengths. The high range resolution requires a wideband waveform of several hundreds of MHz. This paper considers architectures and waveforms for wideband phased array radar and in particular the application of advanced digital adaptive beamforming. A typical wideband waveform used in this class of radar is linear frequency modulation (LFM). It is shown that this waveform is particularly well suited to digital adaptive beamforming. The large electrical aperture demands the use of time delay units for beamsteering, at least at subarray level. A new approach for digitally synthesising the time delay steering is presented. The importance of employing irregular (randomised) subarraying for time delay steering is presented to avoid the problem of wideband grating lobes. This is also a requirement of adaptive beamforming. Finally, an architecture for wideband digital adaptive beamforming which fits well with the use of LFM waveforms is presented.

An enhanced array processing architecture using adaptive digital beamforming at subarray level is proposed for monopulse angle estimation in presence of mainlobe and sidelobe jammings. First, in order to reduce the receiver count, fixed analog beamforming is performed at element level and sub-array outputs are converted to digital signals. Then, adaptive row and column digital beams are formed at subarray level to adaptively cancel multiple jammings. Finally, monopulse sum and delta beamformer follows using row and column beams in vertical and horizontal dimension respectively for elevation and azimuth angle estimation. Compared with the conventional processing with four beams, adaptive digital beamforming is performed with subarray beams prior to sum and delta beamforming, that is, more digital degrees of freedom are exploited. Thus the capability of cancelling multiple electronic jammings simultaneously is provided. Additionally, simulation results of angle estimation are shown. To sum up, this technique is developed to demonstrate the potential of digital beamforming at subarray level with low cost and more facility.

The anti-jamming performance of array systems can be improved markedly by the technique of adaptive digital beamforming (ADBF), which is applied widely in modern radar and communication systems. In linear frequency modulation continuous wave (LFMCW) systems, the target information is usually extracted by range-Doppler processing. In this paper, the application problem of ADBF in the LFMCW system is discussed, and the system schemes of ADBF combining range-Doppler processing are proposed. It is proved that the schemes are feasible and effective, and the signal detection performance can be improved markedly.

The Vehicular Ad Hoc Networks (VANETs) paradigm is a promising technology to enable the Internet of Vehicles (IoV) for future integration with 5G and 6G infrastructures in smart cities. However, VANET can be susceptible to wireless interference, like co-channel interference, which can cause communication quality and performance to deteriorate, threatening vehicular safety applications, including traffic management and accident prevention. Hence, VANET requires practical interference mitigation strategies, such as digital beamforming, that mitigate the signals from unwanted directions while improving the reception of signals from desired directions with adequate precision, which is helpful for VANET’s highly mobile environments. In this paper, a review of the literature on digital beamforming techniques is carried out that examines their advantages and limitations. Furthermore, an important contribution of this paper is the development of an experimental platform for a roundabout VANET based on simulations, where different digital beamforming algorithms, such as phase-shift and Minimum-Variance Distortionless-Response (MVDR), are tested. The results show that the MVDR algorithm leads to improvement due to its adaptability to ad hoc environments. Also, they show thatMVDRadaptive beamforming improves Signal-to-Interference-plus-Noise Ratio (SINR) and reduces outage event proportion compared to non-beamforming and conventional beamforming scenarios, highlighting their potential to mitigate co-channel interference in highly changing VANET environments. Therefore, adaptive digital beamforming can improve the performance and reliability of VANETs, offering the potential for advanced wireless network implementations in smart cities with 5G and 6G infrastructures.

Mitigating ground-clutter signals is one of the major topics for the development of phased array weather radars (PAWRs). Adaptive digital beamforming (DBF) methods have been proposed to reduce ground-clutter effects by making null beam patterns toward the ground. On the other hand, adaptive DBF methods require much higher computational costs than the non-adaptive Fourier DBF method. In the present study, we propose the “precomputed method” for weather radar applications. In this method, a weighting matrix of DBF is once calculated by an adaptive DBF method with observation data recorded in fair weather, and is applied to real-time processing. Since the weighting matrix is not updated in real-time, the computational cost becomes 30 times less than the adaptive DBF, the same level as the Fourier method. At azimuth angles where ground clutter is modest, the results of the Fourier method may be better than those of the proposed method. In those cases, the Fourier method can be used selectively for less ground-clutter regions. This study demonstrates a practical method to reduce the ground-clutter effect of PAWRs by DBF.

The modern technology of radar and mobile communications systems is adaptive digital beam forming. When considering the multicoordinate digital beam forming in radar and communication systems with nonidentical channels of antenna arrays there is a problem of compact matrix record of the receiving channels responses. To solve the given problem it is proposed to operate with a special type of the matrices product, named by the author as penetrated and generalized face-splitting products.

In rough mountainous areas, beam-pointing mismatch problems always arise when a spaceborne Synthetic Aperture Radar (SAR) uses the traditional Digital BeamForming (DBF) approach in elevation to receive echoes, leading to the degradation of the receivers gain and system Signal-to-Noise Ratio (SNR). To solve this problem, an Adaptive Digital BeamForming (ADBF) approach based on the Capon spatial spectrum estimation is proposed. This approach first estimates the Angle Of Arrival (AOA) of the source signal in each range bin using the limited echo data. Then, it updates the weighting vector in the beamforming process, thereby enabling the receiving beams to precisely point to the signal source, and enhance the receivers gain and SNR. Simulation results suggest that the ADBF approach significantly improves the performance compared to the SCan-On-REceive (SCORE) approach, exhibiting robustness to system and source parameters variations.

The Doppler radar has been widely used in respiration detection. However, most of the existing microwave respiration detection works are intended for either a single human subject in front of the radar or multiple subjects with known positions. In this article, a system based on single-input-multiple-output (SIMO) continuous-wave (CW) radar equipped with adaptive digital beamforming (ADBF) technique is presented to detect the respiration of multiple human subjects at unknown positions simultaneously. A solution based on the modified Capon (m-Capon) direction-of-arrival (DOA) estimation and linear constraint minimal variance (LCMV) ADBF is proposed to automatically find the angles of human subjects. By forming spatially distributed beams toward the subjects of interest, human respiration can be remotely obtained. Furthermore, for the detection of each person's respiration, nulls are also generated at the angles of nearby interfering subjects, which results in high target discrimination capability when multiple human subjects are close to each other. The experimental results show good detection accuracy compared with the reference sensor, which verifies the effectiveness of the developed system for multitarget respiration detection.

The wide waveform bandwidths desired for fine range resolution in current and future phased array radars have an impact on the performance of adaptive digital beamforming (ADBF) due to the inevitable frequency response mismatches that occur from channel to channel across the band. In previous work, analytical expressions for the correlation between channels have been developed for a simple two element array with a sinusoidal ripple in either the amplitude or phase response in one of the channels. This paper extends those results to a more general model that allows larger arrays utilizing time delay steering to be modeled. Expressions are developed for the correlation between channels as a function of the parameters of the channel frequency responses. The performance of the adaptive beamformer is characterized with respect to the SINR for waveforms that are flat over the bandwidth and for LFM waveforms processed using stretch processing.

How to improve the performance of Global Navigation Satellite System (GNSS) receiver in purposive interferences and complex electromagnetic environment is a challenge topic. Moreover, the small angle offset in interference direction, which is caused by high-speed relative motion between jammer and receiver makes big trouble for anti-jammering processing. Although some null broadening technics have been proposed to deal with this situation, they all aim at linear array, which is not applicable for practical situation. This paper introduces Generalized Sidelobe Canceller (GSLC) configuration, which is insensitive to array imperfections, and Adaptive Digital Beamforming (ADBF) algorism in circular array to suppress interferences, and formulates the null broadening model in circular condition by correcting covariance matrix, which solve the problem of interference directions mismatch. Simulation results demonstrate that the proposed method could suppress as many interferences as the theoretical maximum and null can be broadened significantly by correcting covariance matrix.

Adaptive digital beamforming is widely used in modern radar and wireless communication systems. Evolutionary algorithms (EA) are powerful tools for more flexible adaptive beamforming. The major drawback of conventional evolutionary algorithms is generally slow in searching for solutions. Bat Algorithm (BA) is a relatively new and faster evolutionary algorithm. In this paper we apply Bat algorithm in adaptive beamforming and also compared its computational efficiency with that of Particle Swarm Optimization (PSO) algorithm which is considered much faster than Genetic Algorithms (GA). Numerical experiments show BA is very efficient, showing a promising tool for adaptive beamforming.

Convolutive blind source separation and adaptive beamforming have similar goals and similar system structure. Both attempt to extract selected source signals from observed sensor mixtures by a filter array. However, time and frequency information are utilized in convolutive blind source separation while spatial information of source signals or sensor array is used in adaptive beamforming. In this paper, we start with a brief introduction of blind source separation and adaptive beamforming. Next, we review approaches combining spatial information used in beamforming with time/frequency processing used in convolutive blind source separation. We also present a new proposed combination approach and simulation results.

– Together with the GPS-based approach, geo-location through mobile communication networks is a key technology for location-based service. To save the cost, most geo-location system is implemented on the existed network service, which has a cellular structure. Still, multilateration is limited in cellular structure because it is difficult for the mobile terminal to acquire distance measurements from multiple base stations. This low hearability in the receiver is caused by co-channel interference and multipath environment. Therefore, hearability enhancement is necessary for multilateration under multipath and interference environment. Former time domain based hearability methods were designed for real signals. However, orthogonal frequency division multiplexing (OFDM) signal, which its usage has been increased in digital wireless communication, is a complex signal. Thus, different hearability enhancement method is needed for OFDM signals. This paper proposes a hearability enhancement method for forward-link multilateration using OFDM signals, which employ interference cancellation and multipath mitigation. A novel interference cancellation and multipath mitigation strategy for complex-valued OFDM signals is presented that has an iterative structure. Simulation results show that the proposed multilateration method provides the user’s position with an accuracy of less than 80m through the mobile WiMAX cellular network in multipath environment. Keywords: OFDM, geo-location, Multilateration, Interference cancellation, Hearability

The output Signal-to-Noise Ratio(SNR) of conventional broadband energy detection is reduced in multi-target and strong interference environment, and the detection performance is great reduced. In order to solve the problem, a broadband detection method based on space-frequency joint optimal filtering which combines subarray STeered Minimum Variance(STMV) broadband adaptive beamforming with Eckart filtering is proposed. Firstly, the spatial adaptive processing is carried out by subarray STMV beamforming, and the optimal filtering is realized in spatial domain by using the interference suppression ability of adaptive beamforming. Then, the power spectrum of signal and noise is estimated by maximum likelihood estimation, and Eckart filter is constructed to assign different weights to the output of adaptive beamforming to maximize the output SNR in frequency domain. The influence of spatial sidelobe interference and noise in the frequency band are reduced to make the output SNR maximum by the proposed method. The broadband detection ability of the target can be effectively improved and the broadband detection performance of passive sonar is also improved. The simulation and experimental data processing results verifiy the effectiveness of the method.

In a multi-vehicle environment, a TT&C (tracking, telemetry and command) system is realized through a unified spread spectrum framework. Adaptive antenna digital beamforming technologies are used to track, measure and command objects. A constant modulus array (CMA) and an adaptive signal canceller estimate the direction of arrival (DOA) of every signal and use the optimum weighted vector to form the beams. The phase-weighted vectors estimated from the DOA improve the processing gain as well as being utilized in transmitting a tele-command signal to form the beam for a specified object. Its processing performance is researched and simulated.