Direction Finding Method Research Articles

A High Precision Direction-Finding Method Based on Multi-Baseline for Target Rescue

Target rescue is an important application in the Internet of Things (IoT), and the direction-finding (DF) is an essential technology for the target rescue. The DF technology based on the phase comparison method is widely used in target rescue. However, due to the phase ambiguity, the phase comparison method is difficult to meet the needs of high precision DF. The long and short baseline method can eliminate the phase ambiguity in a certain angle range, but it cannot accurately direction in all directions. In this article, we propose a high precision DF method based on the multi-baseline and multi-antenna for target rescue. Firstly, the performance of the proposed method in eliminating the inhomogeneity and azimuth ambiguity in single antenna pairs is analyzed theoretically. Then, a measurement system configured of a cycle array with eight antennas is presented to validate the practicability of the proposed method. Finally, the measurement system is verified by experiments conducted in both anechoic chamber and the out-field scenarios. The experiment results demonstrate that the error of the proposed DF method is within 2° in the anechoic chamber and within 5° in out-field. Therefore, the proposed multi-baseline and multi-antenna method can be used for high precision DF for the target rescue.

Method for phase direction finding of signals with asymmetric spectra

The article deals with a new method of phase direction finding of broadband signals with asymmetric spectra. The authors propose a new definition of the signal frequency corresponding to phase measurements in correlation signal processing, such as the correlation-phase frequency.

Narrow-band correlation processing of signals in a phase direction-finding

The article deals with the phase method of direction finding, based on the dependence of the phase difference of the signals received by the antennas, as well as the correlation signal processing in the phase direction finding, which will assess the possibility of signal direction finding of the “Spectrum-RG” spacecraft, derived in the neighborhood of the L2 Lagrange point located at a distance of one and a half million kilometers from Earth.

A novel direction finding algorithm for distributed sources under impulsive noise environments

We extend the bearing estimation algorithm for distributed sources to the impulsive noise scenario that can be modeled as an alpha-stable distributed process. Since the distributed source parameter estimator (DSPE) method is optimized based on the Gaussian model, its performance is severely degraded in the presence of impulsive noise. In this paper, a derivative of the error function-based operator (DEOP) is derived, and a novel direction-of-arrival (DOA) estimation algorithm, namely, DEOP-DSPE, is proposed for distributed sources to suppress the impulsive noise. Meanwhile, to make more effective use of the sensors in the array, we also propose the conjugate co-prime array, which can reduce the number of physical sensors without decreasing the number of estimated target sources. Simulation results demonstrate that the DEOP-DSPE algorithm outperforms the existing direction finding methods for distributed sources in the presence of impulsive noise and illustrate the effectiveness of the conjugate co-prime array.

Ship Detection and Direction Finding Based on Time-Frequency Analysis for Compact HF Radar

Ship detection at the sea surface is important for improving human marine activities. Most existing ship detection methods for high-frequency surface wave radar (HFSWR) are based on peak and constant false alarm rate (CFAR) detection and require a coherent integration time (CIT) of several minutes. However, in such a long period, the target may not be stationary. To account for the nonstationary property, a time-frequency analysis (TFA)-based ship detection and direction finding (DF) method is proposed for HFSWR. Target ridges on the TF representation (TFR) of the echo data are detected first. Next, array snapshots are formed by sampling the extracted ridges and are used to estimate the direction of arrival (DOA). The processing results of the radar data collected at Dongshan, Fujian Province, China, show that the proposed method outperforms the CFAR method with both increased detection rates and decreased DF errors, especially under relatively low signal-to-noise ratio (SNR) scenarios.

Radar with increased angular resolution of objects in wide-angle scanning

The parameters of radar antenna systems constructed according to the traditional scheme with phase shifters inserted both in the transmitting and receiving antenna array with the radar in which signal processing is performed only on the receiving side are considered and compared in the paper. In the second case, an additional requirement of orthogonality of the radiated signals is imposed on the radiating system of the transmitter. The characteristics of the radar with three transmitters and four receivers are compared. Two variants of forming a virtual antenna array are considered. In the first case, the radiation of the linear regular antenna array is analyzed, in the second case the thinned one, but with the same number of emitters. We demonstrate that in the second case, it is possible to implement the radar with a better angular resolution. The features of using the radar as a short-range radar for vehicle security systems with a wide-angle view are elaborated. The possibility of false capture of the target is noted. The authors of the research suggest the unambiguous direction finding method.

Construction of Projection Matrices Based on Non-Uniform Sampling Distribution for AoA Estimation

A Non-Uniform Sampling (NUS) methodology is presented, which improves the Angle of Arrival (AoA) estimation accuracy. The proposed sampling methodology is applied to extract the collected data efficiently and to reduce the possible dependency within rows/columns of the Covariance / Correlation Matrix (CM). The new sampled matrix approach is utilized to form such a projection matrix in order to provide better resolution of angles of arrival for closely incident signals on the antenna array receiver and to increase Degrees of Freedom (DOFs) compared to the classical criterion. The new direction-finding method based on the NUS methodology is called a Non-Uniform Projection Matrix (NUPM). A theoretical analysis is presented to demonstrate the advantage of the NUS methodology in terms of the obtained energy of the eigenvalues that are associated with the signal eigenvectors. It is proved that the proposed matrix sampling approach can provide better estimation resolution and detection of higher numbers of angles of arrival compared to the classical sampling method, without increasing array aperture size and the complexity of computations. A reduced-dimension process is applied to the NUPM in order to decrease the computational burden at the grid-scanning step. A computer simulation, including many scenarios, is implemented to justify the expected improvements of the NUS methodology compared to the classical approach. It is found that the new sampling distribution enhances noise immunity and increases DOFs compared to the conventional criterion. The performance of the NUPM method is compared with several AoA methods, including the Cramer-Rao Lower Bound (CRLB), and the obtained results verify the effectiveness and robustness of the proposed NUPM technique.

Correlation direction finder for small aircraft

Introduction. Small aircraft (SA), or drones, are used in various areas of society, for example, to inspect agriculture and forestry, monitor traffic, and transport small loads. SA are increasingly appearing near airports, power stations, warehouses, and private estates, and may pose a danger to both public and private interests. Detection of SA becomes an urgent problem. The development of SA direction finding devices with given detection characteristics and the predicted detection distance is of practical interest. Theoretical results.For the detection of SA is proposed to use the method of correlation direction finding. Acoustic radiation of a drone is considered as a localized broadband noise process. Interference - acoustic noise in the area of application of the detection means is considered as an isotropic normal process. A comparison of detection characteristics (DC) for the correlation direction finder (CDF) and quadratic detector (QD) is given. The calculated detection parameters demonstrate the advantage of the CDF in signal detection of 6 dB, which leads to an increase in the detection range of the SA. Conclusions.For the detection of drones using acoustic radiation, a correlation direction finder was used. The algorithm for calculating the characteristics of the detection of the noise signal by a correlation direction finder depending on the receiver settings is given. A theoretical comparison of the characteristics of the CDF and QD is given. The gain of the correlation direction finder is established when detecting weak noise signals of approximately 6 dB, which leads to an increase in the detection range. Experimental studies of the direction finding quadcopter Phantom 3 standard correlation receiver confirmed the theoretical prediction.

Wind Direction Estimation Using Small-Aperture HF Radar Based on a Circular Array

Compact high-frequency (HF) antenna arrays are convenient to deploy. However, using a small-aperture HF surface wave radar for wind direction measurement is still a challenging problem, since an unsatisfactory array pattern degrades the performance of Bragg ratio estimation. To address this issue, a digital beamforming method based on a superdirective synthesis technique for an HF receiving array that consists of seven elements positioned on a 5-m diameter circle is proposed. This superdirective beamforming method contains a sidelobe constraint. Subsequently, a hybrid superdirective beamforming and direction-finding method is adopted to estimate the wind direction using a multifrequency HF radar based on a circular array (MHF-C). The superdirective beamforming approach, as well as the wind direction estimation method, is presented in detail. The wind direction estimation method has been applied to the raw data sets that were collected with two MHF-C radars installed along the coast of the East China Sea in April 2015 and comparisons between radar-derived and in situ wind directions have been made. Ship-mounted anemometers were used to obtain in situ measurements at six sampling locations within the overlapping coverage of both radars. Another comparison between the radar-derived and anemometer-derived wind directions, which were obtained from June 15, 2015 to August 12, 2015, has also been made. The results indicate that the proposed method is effective for wind direction estimation with root-mean-square differences (RMSDs) between 24.1° and 33.1°, when wind speeds were higher than 5 m/s. The analysis encourages us to recommend a minimum wind speed of 5 m/s for reasonably assessing wind direction measurement performance.

A Space-Time Coded Mills Cross MIMO Architecture to Improve DOA Estimation and Its Performance Evaluation by Field Experiments

Conventional Mills Cross architecture suffers from poor direction-of-arrival angle estimation accuracy in the dimension that the transmitter is aligned. To improve the estimation accuracy, a space-time coded, multiple-input multiple-output (MIMO) direction finding method, with complementary codes is presented. The performance of the suggested MIMO Mills Cross architecture has been evaluated by underwater field experiments. Field experiments confirm the feasibility of the proposed approach and illustrate the performance gains. Since the proposed approach does not require any changes in the conventional Mills Cross hardware, the performance improvement can also be realized by a software reconfiguration for existing legacy systems.

Uniform Sampling Methodology to Construct Projection Matrices for Angle-of-Arrival Estimation Applications

This manuscript firstly proposes a reduced size, low-complexity Angle of Arrival (AoA) approach, called Reduced Uniform Projection Matrix (RUPM). The RUPM method applies a Uniform Sampling Matrix (USM) criterion to sample certain columns from the obtained covariance matrix in order to efficiently find the directions of the incident signals on an antenna array. The USM methodology is applied to reduce the dependency between the adjacent sampled columns within a covariance matrix; then, the sampled matrix is used to construct the projection matrix. The size of the obtained projection matrix is reduced to minimise the computational complexity in the searching grid stage. A theoretical analysis is presented to demonstrate that the USM methodology can increase the Degrees of Freedom (DOFs) with the same aperture size and number of sampled columns compared to the classical sampling criterion. Then, a polynomial root is constructed as an alternative efficient computational solution of the UPM method in a one-dimensional (1D) array spectrum peak searching problem. It is found that this distribution increases the number of produced nulls and enhances noise immunity. The advantage of the RUPM method is that it is appropriate to apply for any array configuration while the Root-UPM offers better estimation accuracy with less execution time under a uniform linear array condition. A computer simulation based on various scenarios is performed to demonstrate the theoretical claims. The proposed direction-finding methods are compared with several AoA methods in terms of the required execution time, Signal-to-Noise Ratio (SNR) and different numbers of data measurements. The results verify that the new methods can achieve significantly better performance with reduced computational demands.

Fourth-order direction finding in antenna arrays with partial channel gain/phase calibration

In this paper, we consider the problem of direction finding in partly calibrated uniform linear array (ULA) system with channel gain/phase mismatch, by taking advantage of the high-order statistics (HOS) of the array observations. In particular, we devise a (2M−1)×(2M−1) fourth-order cumulant (FOC) matrix for an M-element ULA and exploit it to estimate the directions-of-arrival (DOAs) with subspace techniques. The proposed FOC direction finding method is computationally attractive without spatial spectrum search and robust against spatially correlated noise. It is also able to achieve better DOA estimation performance than the existing method, as illustrated by numerical simulations.

Radio interferometric location finding of VLF signal transmitters

The article presents some experimental results of using a very low frequency (VLF) interferometer designed in INRTU for radio direction finding of VLF transmitters. It is evaluated that amplitude angular-position measurements provides azimuth accuracy of several degrees. Distant VLF stations (3000 – 5500 km) can be located in a 2-6 km area if the signal azimuth is known with 0.001° accuracy. In order to minimize errors associated with antenna’s angular offset the authors developed a correcting algorithm. Using both radio direction finding methods and additional geophysical data (year and daily variations of solar terminator moving, signal disturbances during solar flares) the authors ascertained that 24.1 kHz and 25.0 kHz signals are emitted from the transmitter in Mokpo (South Korea). The phase measurements give about two times lower error of 1.5–2° for the NWC station (19.8 kHz, Australia) which is located more than 8200 km away from the VLF interferometer.

Non‐analytical direction‐finding method as a key step in pursuing low size, weight, costs, and computational power in the deinterleaving of radar pulses

The study presents a direction-finding method that is not limited to the main lobe zones of antenna patterns. The technique allows for the angular sector of interest to be divided by few channels, pursuing low size, weight, costs, and computational power in radar detection. Experiments done on a building rooftop have shown that, with a minimum of 150 processed pulses, the distributions of estimates of direction of arrival are well behaved, with a relationship between standard deviation and signal-to-noise ratio. As a result, information is provided that may soften the deinterleaving of radar pulses.

Statistical model and analysis of two-scale modification of conical scanning direction finding method

Statistical analysis method and its results are presented for a two-scale modification of the conical scanning direction finding method generalizing it for a case of elliptical cross-section of antenna beam. In order to utilize additional positional information that is excluded in a typical implementation of conical scan method, a two-scale procedure is proposed for estimating the direction to object. It is shown, that application of this procedure does not lead to worsening of the accuracy of object’s coordinates estimate near boresight axis and also attains a significant increase of angular operating area of direction finding due to the increase in number of harmonics of conical scanning frequency included in processing. Analytical expressions are obtained and discriminator and fluctuation curves are calculated, revealing the possibilities to increase the angular operating area of direction finding depending on signal-to-noise ratio and ellipticity of antenna beam’s cross-section.

Spatial time-frequency distribution of cross term-based direction-of-arrival estimation for weak non-stationary signal

In the radar array signal processing direction of arrival (DOA), the estimation of weak non-stationary signal is an important and difficult problem when both strong and weak signals are coexisting particularly because the weak non-stationary signals are often submerged in noise. In this paper, we proposed a novelty method to estimate the direction of arrival (DOA) of weak non-stationary signal in scenario for strong non-stationary interference signals and Gaussian white noise. The method utilizes spatial time-frequency distribution (STFD) of cross terms rather than suppressing cross terms in time-frequency analysis. The STFD of cross terms are introduced as an alternative matrix, which is similar to data covariance matrix in multiple signal classification (MUSIC), for the DOA estimation of a weak non-stationary signal. The cross-term amplitude of the strong and weak signals is usually above the noise and is easier to use than the auto-term of the weak signal. In the cross term, the information of the weak signal is included, and the auto-term of these weak signals is difficult to extract directly. The ability to incorporate the STFD of cross terms empowers information about a weak non-stationary signal for DOA estimation, leading to improved signal estimates for direction finding. The method based on the STFD of cross terms for DOA estimation of the weak non-stationary signal is revealed to outperform the time-frequency MUSIC and traditional MUSIC algorithm by simulation, respectively. This method has the advantages of the time-frequency direction finding method and also deals with the situation of weak signals. When the strong and weak signals exist at the same time and the two angles are similar, the cross-terms can be used to perform DOA estimation on the weak signal.

OPTIMIZATION OF DIRECT DIGITAL METHOD OF CORRELATIVE-INTERFEROMETRIC DIRECTION FINDING WITH RECONSTRUCTION OF SPATIAL ANALYTICAL SIGNAL

Context. At present, in automated radio monitoring systems, direction-finding of radio-electronic means is carried out under conditions of a complex electromagnetic environment, a large apriori uncertainty about the parameters of radio emissions, as well as real-time implementation. A promising direction for these conditions is the use of broadband correlation-interferometric radiodirection finders using digital processing of the complex spectrum of the received mixture of radio emissions.Objective. The aim of the article is to study and optimize the direct digital method of correlation-interferometric direction finding with reconstruction of the spatial analytical signal.Method. The paper analyzes the features of the implementation and accuracy of the direction-finding method studied, as well as analytical optimization of the non-exploratory digital method of correlation-interferometric direction finding with reconstruction of the spatial analytical signal.Results. The parameters that are included in the dispersion equation for the error in estimating the direction to the radio source for the non-exploratory digital method of correlation-interferometric direction finding with reconstruction of the spatial analytical signal that are to be optimized are determined. It is shown that the main parameters that it is advisable to optimize are the separation distance between the selected elements of the antenna array, for the spatial positions of which the complex analytical signal is reconstructed, and their numbers. A theoretical optimization of the parameters of the studied method, as well as a comparative analysis of analytical calculations and simulation results were carried out. As a result of modeling, the dependence of the method error of the bearing estimate and of the average square estimate of the bearing under the action of normal Gaussian noise on thevalues of the optimized parameters was obtained.Conclusions. A theoretical optimization of the parameters of the studied method has been carried out and it has been determined that it is advisable to use the symmetric separation of the 64-element antenna array by 28 steps to minimize the variance of the error in estimating the direction to the radiation sourse and to ensure maximum accuracy of direction finding.

Improving Surface Current Resolution Using Direction Finding Algorithms for Multiantenna High-Frequency Radars

AbstractWhile land-based high-frequency (HF) radars are the only instruments capable of resolving both the temporal and spatial variability of surface currents in the coastal ocean, recent high-resolution views suggest that the coastal ocean is more complex than presently deployed radar systems are able to reveal. This work uses a hybrid system, having elements of both phased arrays and direction finding radars, to improve the azimuthal resolution of HF radars. Data from two radars deployed along the U.S. East Coast and configured as 8-antenna grid arrays were used to evaluate potential direction finding and signal, or emitter, detection methods. Direction finding methods such as maximum likelihood estimation generally performed better than the well-known multiple signal classification (MUSIC) method given identical emitter detection methods. However, accurately estimating the number of emitters present in HF radar observations is a challenge. As MUSIC’s direction-of-arrival (DOA) function permits simple empirical tests that dramatically aid the detection process, MUSIC was found to be the superior method in this study. The 8-antenna arrays were able to provide more accurate estimates of MUSIC’s noise subspace than typical 3-antenna systems, eliminating the need for a series of empirical parameters to control MUSIC’s performance. Code developed for this research has been made available in an online repository.

Direction Finding of Linear Frequency Modulation Signal in Time Modulated Array With Pulse Compression

A novel direction-finding method with time-modulated array (TMA) is proposed for modulating the echo linear frequency modulation (LFM) signal and analyzing its harmonic characteristics. Unlike conventional analysis method where each coefficient of harmonic components is analyzed by discrete Fourier transform, in the proposed method, the harmonic coefficients of modulated signals are calculated by using the pulse compression technology. After the modulated LFM signal is compressed by the matched filter, a closed-form expression of the corresponding output signal is derived and the harmonic coefficients of the input modulated signals can also be obtained. Meanwhile, in order to avoid being affected by other harmonic components in the process of analyzing each harmonic coefficient, the constraints to acquire independent harmonic coefficients are highlighted. Numerical simulations are provided to verify the performance of the proposed method, and a simple S-band eight-element TMA is constructed to experimentally verify its feasibility.

Robust Direction-Finding Method for Sensor Gain and Phase Uncertainties in Non-uniform Environment

A direction-of-arrival (DOA) estimation algorithm, which is robust to sensor gain and phase uncertainties for completely uncalibrated arrays in a non-uniform noise environment, is proposed in this study. As a result of the sensor gain uncertainties or the shielding effects for some baffled arrays, the noise power may vary with sensors. Therefore, a non-uniform noise model is considered. A cost function established by the orthogonality of subspaces is accumulated along several rough space intervals surrounding the real angles of sources. After analyzing the influences of rough space intervals, an iterative refinement operation is carried out to improve the estimation performance of the DOA and sensor gain and phase responses. The Cramer–Rao bounds of the DOA and sensor gain and phase in the non-uniform noise model are derived. Simulations and experimental results show the superiority of the proposed method.