Angle Of Arrival Measurements Research Articles

Simultaneous frequency and angle-of-arrival measurement of microwave signals utilizing the Talbot effect and pulse interference

We propose and demonstrate a simple and efficient scheme for simultaneous frequency and angle-of-arrival (AOA) measurement of microwave signals using the Talbot effect and pulse interference. This method maps the frequency of the microwave signal to the time intervals of output pulses through the Talbot effect, using a specialized sampling and dispersive structure. Concurrently, the phase difference related to the AOA is encoded onto the relative amplitudes of the output pulses via pulse interference. By analyzing both the time intervals and relative amplitudes of the output pulses, precise frequency and AOA values of the microwave signal are simultaneously derived. Simulation results indicate that the system can perform real-time, gap-free frequency and AOA measurements of multiple signals. Proof-of-concept experiments show this method achieves high accuracy, with AOA measurement errors within ±2.9° over a range of −63° to 63°, and frequency measurement errors within ±60 MHz for frequency bands of 2–3 GHz and 12–13 GHz.

A Dual-Branch Convolutional Neural Network-Based Bluetooth Low Energy Indoor Positioning Algorithm by Fusing Received Signal Strength with Angle of Arrival

Indoor positioning is the key enabling technology for many location-aware applications. As GPS does not work indoors, various solutions are proposed for navigating devices. Among these solutions, Bluetooth low energy (BLE) technology has gained significant attention due to its affordability, low power consumption, and rapid data transmission capabilities, making it highly suitable for indoor positioning. Received signal strength (RSS)-based positioning has been studied intensively for a long time. However, the accuracy of RSS-based positioning can fluctuate due to signal attenuation and environmental factors like crowd density. Angle of arrival (AoA)-based positioning uses angle measurement technology for location devices and can achieve higher precision, but the accuracy may also be affected by radio reflections, diffractions, etc. In this study, a dual-branch convolutional neural network (CNN)-based BLE indoor positioning algorithm integrating RSS and AoA is proposed, which exploits both RSS and AoA to estimate the position of a target. Given the absence of publicly available datasets, we generated our own dataset for this study. Data were collected from each receiver in three different directions, resulting in a total of 2675 records, which included both RSS and AoA measurements. Of these, 1295 records were designated for training purposes. Subsequently, we evaluated our algorithm using the remaining 1380 unseen test records. Our RSS and AoA fusion algorithm yielded a sub-meter accuracy of 0.79 m, which was significantly better than the 1.06 m and 1.67 m obtained when using only the RSS or the AoA method. Compared with the RSS-only and AoA-only solutions, the accuracy was improved by 25.47% and 52.69%, respectively. These results are even close to the latest commercial proprietary system, which represents the state-of-the-art indoor positioning technology.

Robust Bluetooth AoA Estimation for Indoor Localization Using Particle Filter Fusion

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most cellular systems, such as Bluetooth indoor positioning systems, due to multipath and non-line-of-sight (NLOS) propagation, indoor positioning accuracy is severely affected. In this paper, a comprehensive algorithm that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates is investigated, which is obtained using particle filtering. This algorithm allows us to explore new optimized methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by approximately 25.7% on average.

Indoor position estimation using angle of arrival measurements: An efficient multi-anchor approach with outlier rejection

This paper addresses the inherent nonlinear problem in indoor position estimation utilizing Angle of Arrival (AoA) measurements. We investigate the influence of deployment geometry on system performance through both analytical methods and Monte-Carlo simulations, shedding light on the limitations of single and multi-anchor setups and underscoring the imperative for advanced multi-anchor localization methods. In response to this problem, we propose a multi-anchor solution with outlier rejection that efficiently considers the nonlinearity of the model. For each anchor, our approach approximates the probability distribution of the node position by leveraging a geometrically-derived unscented transformation of AoA estimates. The approximations are then integrated into a majority voting scheme, effectively eliminating outliers induced by multipath or other adverse effects. To derive the final enhanced position estimate, Bayesian inference is applied to fuse the selected information. Finally, the efficacy of the solution is validated conducting a comparative analysis against commonly used approaches in a real-world Bluetooth indoor localization system. The results obtained solely from high-level angular measurements underscore the practicality, robustness and high accuracy of the proposal.

UAV Path Optimization for Angle-Only Self-Localization and Target Tracking Based on the Bayesian Fisher Information Matrix.

In this paper, new path optimization algorithms are developed for uncrewed aerial vehicle (UAV) self-localization and target tracking, exploiting beacon (landmark) bearings and angle-of-arrival (AOA) measurements from a manoeuvring target. To account for time-varying rotations in the local UAV coordinates with respect to the global Cartesian coordinate system, the unknown orientation angle of the UAV is also estimated jointly with its location from the beacon bearings. This is critically important, as orientation errors can significantly degrade the self-localization performance. The joint self-localization and target tracking problem is formulated as a Kalman filtering problem with an augmented state vector that includes all the unknown parameters and a measurement vector of beacon bearings and target AOA measurements. This formulation encompasses applications where Global Navigation Satellite System (GNSS)-based self-localization is not available or reliable, and only beacons or landmarks can be utilized for UAV self-localization. An optimal UAV path is determined from the optimization of the Bayesian Fisher information matrix by means of A- and D-optimality criteria. The performance of this approach at different measurement noise levels is investigated. A modified closed-form projection algorithm based on a previous work is also proposed to achieve optimal UAV paths. The performance of the developed UAV path optimization algorithms is demonstrated with extensive simulation examples.

Photonic architecture for remote multi-parameter measurement and transmission of microwave signals

A photonic architecture for remote multi-parameter measurement and transmission of microwave signals is proposed and demonstrated, which utilizes a dual-parallel dual-drive Mach-Zehnder modulator (DP-DDMZM) in the antenna unit and a dual-drive Mach-Zehnder modulator (DDMZM) in the processing unit. Doppler frequency shift (DFS) and angle of arrival (AOA) can be determined by analyzing the down-converted intermediate frequency signals. Introducing a reference signal in the processing unit ensures DFS measurement without directional ambiguity. The proposed architecture can also be applied for instantaneous frequency measurement based on down-conversion. Due to the use of optical single sideband modulation, long-distance transmission of radio frequency (RF) signals without dispersion-induced power fading can be achieved. Experiments for accurate and stable DFS and AOA measurement as well as long-distance RF signal transmission with dispersion-induced power fading are presented. The approach avoids the use of optical filters and polarization-related devices, facilitating wideband and stable operation, which is highly desirable. The proposed architecture is a potential solution for microwave photonic antenna remoting, offering support for both remote transmission and multi-parameter measurement.

Photonics-assisted simultaneous frequency and angle-of-arrival measurement using parameter mapping method

A photonics-assisted simultaneous frequency and angle of arrival (AOA) measurement system based on parameter mapping method is proposed and demonstrated by simulation and experiment. Using optical sideband sweeping and envelope detection, the frequencies of the signals under test (SUT) are mapped to the time domain of the output amplitude of the electrical pulses, and the AOA-dependent phase differences are mapped to the amplitudes of the output electrical pulses. The experiment achieved multiple-frequency signal measurements, and the absolute measurement error was between 1.8 MHz and 5.4 MHz in the range from 9.4 GHz to 13 GHz. The frequency range can be adjusted by modifying the bandwidth of the frequency-swept signal or the DC bias voltage. Furthermore, the unambiguous AOA measurement from −90° to 90° is successfully realized simultaneously, and the error of the AOA measurement ranging from −66.44° to 66.44° is confined to within ±1.4°. Due to its robustness and flexibility, this dual-function measurement system can find various applications in future electronic warfare systems.

Photonic Measurement for Doppler Frequency Shift and Angle of Arrival Based on Integrated Dual-Parallel Dual-Drive Modulator

A microwave photonic Doppler frequency shift (DFS) and angle of arrival (AOA) measurement method based on a dual-parallel dual-drive Mach–Zehnder modulator (DP-DDMZM) is proposed and demonstrated. A sawtooth wave signal is used to drive the DC port of the modulator to realize the optical frequency shift, and thus the direction discrimination of DFS is realized. Due to single-sideband modulation, the proposed system can avoid periodic power fading and the separation of the remote antenna unit (RAU) and central office (CO) can be achieved. In the experiment, the microwave DFS is estimated with a clear direction and a maximum measurement error of 0.25 Hz over an ultrawide operation frequency from 6 to 36 GHz. The experiment also proves that the phase error of AOA measurement is less than 1.5 degrees. Compared with the traditional electronic microwave measurement scheme, the proposed scheme has great competitive advantages in future broadband electronic applications due to the features of multifunction, large bandwidth and anti-interference.

Dual-UAV Collaborative High-Precision Passive Localization Method Based on Optoelectronic Platform

Utilizing the optical characteristics of the target for detection and localization does not require actively emitting signals and has the advantage of strong concealment. Once the optoelectronic platform mounted on the unmanned aerial vehicle (UAV) detects the target, the vector pointing to the target in the camera coordinate system can estimate the angle of arrival (AOA) of the target relative to the UAV in the Earth-centered Earth-fixed (ECEF) coordinate system through a series of rotation transformations. By employing two UAVs and the corresponding AOA measurements, passive localization of an unknown target is possible. To achieve high-precision target localization, this paper investigates the following three aspects. Firstly, two error transfer models are established to estimate the noise distributions of the AOA and the UAV position in the ECEF coordinate system. Next, to reduce estimation errors, a weighted least squares (WLS) estimator is designed. Theoretical analysis proves that the mean squared error (MSE) of the target position estimation can reach the Cramér–Rao lower bound (CRLB) under the condition of small noise. Finally, we study the optimal placement problem of two coplanar UAVs relative to the target based on the D-optimality criterion and provide explicit conclusions. Simulation experiments validate the effectiveness of the localization method.

Evolutionary Tracking Algorithm Based on Combined Received Signal Strength and Angle of Arrival Measurements in Wireless Sensor Networks

Evolutionary Tracking Algorithm Based on Combined Received Signal Strength and Angle of Arrival Measurements in Wireless Sensor Networks

Photonic angle-of-arrival measurement of microwave signals using a triangular wave.

A novel, to the best of our knowledge, photonics-assisted approach for measuring the angle-of-arrival (AOA) of microwave signals with a large measurement range is proposed. The system utilizes a dual-drive Mach-Zehnder modulator (DDMZM) for signal modulation, followed by an optical filter for sideband selection. The dc port of the DDMZM is fed by a triangular wave to generate a pair of opposite frequency shifts. An intermediate frequency (IF) signal with a periodic phase jump is obtained after photodetection. The AOA of the incoming signals can be estimated by measuring the value of the phase jump. The key novelty of the proposed scheme lies in the application of a triangular wave to shift the frequency of optical signals, which introduces a periodic phase jump to the IF signal. The system incorporates only a single optical channel, largely reducing the system complexity. Experimental results show that an AOA measurement with a range of -70.8° to 70.8° is realized, with errors confined to within ±2°.

Single-channel system for joint unambiguous measurement of DFS and AOA based on serrodyne modulation.

In this paper, a photonic-assisted system for simultaneous and unambiguous measurement of the Doppler frequency shift (DFS) and angle-of-arrival (AOA) using a dual-parallel dual-drive Mach-Zehnder modulator (DP-DDMZM) is proposed and investigated. The echo signals received by two receiving antennas are applied to the radio frequency ports of one sub-DDMZM of the DP-DDMZM. The bias port of the sub-DDMZM is fed by a binary electrical signal that is used to construct two different mapping curves on the relationship between the phase difference and the power of the output intermediate frequency (IF) signal. Therefore, unambiguous AOA measurement with extended range can be realized. The transmitted signal is input into the other sub-DDMZM to implement single-sideband modulation, which is then frequency shifted based on serrodyne modulation. Both the value and direction of DFS can be derived intuitively from the frequency of the output IF signal. Simulation results show that the measurement error of unambiguous DFS measurement is no more than ±0.008H z in the range of -100k H z to 100kHz, and the measurement error of unambiguous AOA is less than ±0.2∘ in the range of -70.8∘ to 70.8°. Moreover, since the scheme does not involve the construction of multi-channels or use of any filter or polarization dependent device, the system has concise structure, high accuracy, large operating bandwidth, and strong robustness, and can be considered as a very promising solution for actual applications.

A robust lp‐norm localization of moving targets in distributed multiple‐input multiple‐output radar with measurement outliers

AbstractThe Gaussian noise model and estimators based on least squares (LS) are widely used in target localisation with distributed multiple‐input multiple‐output (MIMO) radar because of their computational efficiency. However, the accuracy of existing LS‐based target localisation algorithms deteriorates sharply in the presence of outliers in the measurements. Thus, a robust solution is developed based on the ‐norm minimisation criterion and iteratively reweighted least squares (IRLS) for locating a moving target with impulse noise using the angle of arrival (AOA), time delay (TD), and Doppler shift (DS) measurements. First, the AOA, TD, and DS measurement noise models are developed based on the α‐stable distribution. Then, the localisation problem is transformed into an ‐norm minimisation problem by linearising the AOA, TD, and DS measurement equations. Finally, the ‐norm minimisation problem is solved using an IRLS method to obtain the target position and estimate the velocity. Moreover, the optimum of the norm order (p) and the Cramér–Rao lower bound for the target position and velocity estimation are derived under α‐stable distributed measurement noise. The simulation results demonstrate that the developed algorithm offers higher accurascy and robustness than the existing ones in the presence of measurement outliers.

An Efficient Hybrid Multi-Station TDOA and Single-Station AOA Localization Method

Multi-station passive localization algorithms based on hybrid Time Difference of Arrival (TDOA) and Angle of Arrival (AOA) have been thoroughly studied. But it usually requires each station to obtain the AOA of the source and relies on the precise station position. These conditions are generally not satisfied in practical applications. In addition, the geometry between the source and these stations also affects the localization accuracy. This paper studies the passive source localization problem based on multi-station TDOA and single-station AOA measurements. First, we propose a closed-form solution source localization method based on multi-station TDOA and single-station AOA measurements, which requires only the reference station used to calculate TDOA to be able to observe the AOA measurements of the source. It solves the problem of hybrid localization of different numbers of TDOA and AOA measurements. Theoretical analysis proves that the performance of the proposed method can reach the Cramer-Rao Lower Bound (CRLB) under small noise conditions. Then, we model the relationship between the position of each station relative to the source and the localization accuracy. Through the D-optimality criterion, we obtain the optimal geometry between multiple stations and the source Simulation results confirm the validity of these theories.

Hybrid TOA-AOA WLS Estimator for Aircraft Network Decentralized Cooperative Localization

Cooperative localization is widely used to solve the network localization problem in global navigation satellite system (GNSS) denied environments. In particular, gathering the measurement results of all nodes on a specific node requires substantial time for aircraft networks. Therefore, methods simultaneously calculating all the target node positions are challenging to apply due to information delay. This study uses only two hops measurements information relying on the time of arrival (TOA) and angle of arrival (AOA) to propose a weighted least squares (WLS) method that decentralizes the calculation of a specific single target node position in a 3D environment. Moreover, the effect of TOA and AOA measurement errors on localization accuracy is analyzed based on the geometric relationship. Consequently, a novel weight-factor calculation method is designed. The simulation results show that the proposed cooperative localization method can improve localization accuracy compared with the decentralized non-cooperative method. Furthermore, the proposed hybrid approach provides superior localization accuracy than the weight-factor calculation method which only considers the distance.

3-D Hybrid RSS-AoA Passive Source Localization With Unknown Path Loss Exponent

The use of Received Signal Strength (RSS) mea- surements for passive localization is a simple and versatile method in Wireless Sensor Networks (WSNs). Another commonly used method is based on Angle of Arrival (AoA) measure- ment. Combining these two methods (RSS-AoA) can enhance the reliability of localization. In this letter, we investigate the localization problem (using joint RSS and AoA measurements) when the Path Loss Exponent (PLE) is unknown and only some of the nodes are anchors with known locations. When PLE is unknown, localization performance is affected. Therefore, we propose a joint estimation method for source location and PLE using an iterative Weighted Least Square (WLS) estimation. Simulation results show that our proposed method outperforms other competing algorithms in terms of localization accuracy.

Algorithm for Topology Search Using Dilution of Precision Criterion in Ultra-Dense Network Positioning Service Area

User equipment (UE) location estimation in emerging 5G/B5G/6G Ultra-Dense Networks (UDNs) is a breakthrough technology in future wireless info-communication ecosystems. Apart from communication aspects, network infrastructure densification promises significant improvement in UE positioning accuracy. Unlike networks of previous generations, an increased number of gNodeBs (gNBs) per unit area and/or volume in UDNs allows to perform measurements for UE positioning only with those base stations whose topologies are most suitable from the geometric point of view. Quantitative measurements of gNB topology suitability include horizontal (HDOP), vertical (VDOP), and position (PDOP) dilution of the precision (DOP) criteria on the plane, in height, and in space, respectively. In the current work, we formalize a set of methods for gNB topology search using time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and combined TOA–AOA and TDOA-AOA measurements. The background of the topology search using DOP criteria is a significantly increased number of gNBs per unit volume in UDNs. Based on a simulation, we propose a novel approach for a topology search in a positioning service area, resulting in a PDOP less than one for the Gazprom Arena with only five gNBs. The contribution of the current research includes algorithm and software for an iterative search of all possible gNB and UE locations in space, minimizing UE geometric DOP. The practical application of the algorithm is the gNB topology substantiation for the given positioning scenarios in 5G/B5G/6G UDNs.

Photonics-Based Simultaneous DFS and AOA Measurement System without Direction Ambiguity

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals based on a single photonic system is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3 × 10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are successfully realized simultaneously. It is compact and cost-effective, as well as has enhanced system stability and improved robustness for modern electronic warfare systems.

Simultaneous and unambiguous identification of DFS and AOA without dependence on echo signal power.

We present a photonics-based method of estimating Doppler frequency shift (DFS) and angle of arrival (AOA). The proposed identification method for the DFS and AOA is simultaneous and unambiguous. A reference radio frequency signal is introduced to realize the frequency downconversion. By monitoring the frequency of the downconverted signals generated after the photodetection, the direction ambiguity of the DFS is canceled out. The AOA can be instantaneously calculated through two downconverted signals via a Hilbert transform. Experimental results verify that a -77.90° to 77.90° AOA measurement with errors of less than ±1° is implemented, and a DFS measurement with errors of no more than ±3.1 Hz is also realized. Our proposed method not only removes the direction ambiguities of both DFS and AOA, but also avoids the dependence on echo signal power in AOA measurement, which largely increases the feasibility in realistic applications.

Photonic approach for Doppler-frequency-shift and angle-of-arrival measurement with direction unambiguity and high precision.

A novel, to the best of our knowledge, scheme based on a dual-drive Mach-Zehnder modulator (DDMZM) is proposed for Doppler-frequency-shift (DFS) and angle-of-arrival (AOA) measurement without direction ambiguity. The echo signal from one antenna is coupled with a local oscillator and then fed into the upper RF port of the DDMZM, and the echo signal from the other one is directly fed to its lower RF port. The generated two first-order optical sidebands are separated by an interleaver to form two channels and then detected by two identical low-speed photodiodes, and so both magnitude and orientation of the AOA and DFS can be deduced from the power and frequency of the beating signals. The AOA measurement without direction ambiguity can be achieved by comparing the power of beating signals from two channels. In addition, through operating the DDMZM at different transmission points for different AOA measurement ranges, the range of high-precision AOA measurement can be extended. The system has the low complexity and high stability because only a DDMZM is used. The simulation results demonstrate the measurement of the DFS in the range of 500kHz with errors <0.05H z and the AOA from -90∘ to +90∘ with error <0.8∘.