Reference Waveform Research Articles

Range selective digital holographic imaging of vibrating objects using FMCW lidar

The use of frequency modulated continuous wave (FMCW) chirped transmit and reference waveforms in digital holographic (DH) imaging has enabled range selectivity. By frequency shifting the reference beam to compensate for the typical FMCW lidar beat frequency associated with a particular range, a temporally stable holographic image is formed for objects at the selected range and coherently integrates on a short wave infrared (SWIR) sensor. For vibrating objects, longitudinal movements of the object greater than half of an optical wavelength during the exposure time of the sensor array induce phase shifts that can wash out the hologram. An analog feedback system was designed and constructed whereby a lidar subassembly provides real time phase compensation information to a DH subassembly in order to stabilize the range selective digital holographic recording of the object. The design and characterization of the feedback system, as well as the results demonstrating the performance for vibrating objects that move over 17 wavelengths during the sensor exposure, are discussed.

Acoustic frequency-based method for high-speed aircraft combustion analysis and hybrid artificial intelligence diagnostics

In the paper, a method of high-speed continuous combustion monitoring for jet aircrafts, based on acoustic data processing, is proposed. As part of the research, acoustic signals corresponding to the specific phases of the combustible mixture formation and its combustion were separated. They were assigned to the generated process energy value. In the result, parametric functions were obtained in multidimensional spaces of states and processes. Parameters and acoustic characteristics in the amplitude, frequency and JTFA domains constituted information about particular symptoms in the jet engine, thanks to which reference waveforms of signals and forms for specific malfunctions were mapped. The above graphic characteristics have been parameterized to determine their diagnostic reliability factors.The method is verified by empirical signals obtained from turbojet propulsion system in time and power dependent conditions. Appropriate exothermic combustion phases were assigned for the determined acoustic spectra, taking into account the obtained power. Then, representative diagnostic parameters transformed in the process values domain were calculated. Finally, monitoring functions and algorithms of combustion efficiency with determination of malfunctions sources (at dynamic conditions) are proposed.As a result, it is possible to identify first outbreaks of design and process failures during fuel injection and combustion in aircrafts, taking into account artificial intelligence methods. The obtained results indicate it is possible to adapt the acoustic characteristics of the spectra and their discrete representatives, for appropriate states and failures, to detect first dangerous symptoms in the aircraft during flight conditions (supporting OBD with the acoustic adaptive diagnostic procedures).

Enhancing Sustainable Transportation with Advancements in Photonic Radar Technology with MIMO and IIR Filtering for Adverse Weather Conditions

Sustainable transportation is crucial in addressing global road safety and environmental challenges. This study introduces a novel photonic radar system, leveraging Linear Frequency-Modulated Continuous Wave (LFMCW) technology for high-speed data transmission. Operating in a homodyne configuration, this system uses a single oscillator to generate both signal and reference waveforms. It incorporates mode division multiplexing (MDM) to enable the detection and ranging of multiple targets, even under adverse atmospheric conditions. To counter atmospheric attenuation, the system is equipped with a 2 × 2 MIMO technique and an Infinite Impulse Response (IIR) filter. Numerical simulations demonstrate the system’s superior performance in range resolution and target detection, achieving significant power improvements. The IIR filter further enhances detection, achieving a power improvement of 200% for target 1 and 276% for target 2. With low power requirements and enhancement through IIR filter equalization, this system presents a viable option for battery-operated vehicles. This innovative approach offers a low-power high-efficiency solution suitable for battery-operated vehicles, promoting safer and more reliable sustainable transportation.

Computing pulsatile blood flow of coronary artery under incomplete boundary conditions

BackgroundAccurate measurement of pulsatile blood flow in the coronary arteries enables coronary wave intensity analysis, which can serve as an indicator for assessing coronary artery physiology and myocardial viability. Computational fluid dynamics (CFD) methods integrating coronary angiography images and fractional flow reserve (FFR) offer a novel approach for computing mean coronary blood flow. However, previous methods neglect the inertial effect of blood flow, which may have great impact on pulsatile blood flow calculation. To improve the accuracy of pulsatile blood flow calculation, a novel CFD based method considering the inertia term is proposed. MethodsA flow resistance model based on Pressure-Flow vs.Time curves is proposed to model the resistance of the epicardial artery. The parameters of the flow resistance model can be fitted from the simulated pulsating flow rates and pressure drops of a specific mode. Then, pulsating blood flow can be calculated by combining the incomplete pressure boundary conditions under pulsating conditions which are easily obtained in clinic. Through simulation experiments, the effectiveness of the proposed method is validated in idealized and reconstructed 3D model of coronary artery. The impacts of key parameters for generating the simulated pulsating flow rates and pressure drops on the accuracy of pulsatile blood flow calculation are also investigated. ResultsFor the idealized model, the previously proposed Pressure-Flow model has a significant leading effect on the computed blood flow waveform in the moderate model, and this leading effect disappears with the increase of the degree of stenosis. The improved model proposed in this paper has no leading effect, the root mean square error (RMSE) of the proposed model is low (the left coronary mode:≤0.0160, the right coronary mode:≤0.0065) for all simulated models, and the RMSE decreases with an increase of stenosis. The RMSE is consistently small (≤0.0217) as the key parameters of the proposed method vary in a large range. It is verified in the reconstructed model that the proposed model significantly reduces the RMSE of patients with moderate stenosis (the Pressure-Flow model:≤0.0683, the Pressure-Flow vs.Time model:≤0.0297), and the obtained blood flow waveform has a higher coincidence with the simulated reference waveform. ConclusionsThis paper confirms that ignoring the effect of inertia term can significantly affect the accuracy of calculating pulsatile blood flow in moderate stenosis lesions, and the new method proposed in this paper can significantly improves the accuracy of calculating pulsatile blood flow in moderate stenosis lesions. The proposed method provides a convenient clinical method for obtaining pressure-synchronized blood flow, which is expected to facilitate the application of waveform analysis in the diagnosis of coronary artery disease.

Study of Simple Prediction Method for Road Traffic Vibration from viaducts

On Prediction of Road Traffic Vibration of INCE/J Technical Subcommittees, we are studying the creation of prediction formulas for vibration from embankments and cuts and vibration from bridges. This paper presents the concept of a simplified method for predicting road traffic vibration from viaducts. When large vehicle runs on viaduct, vibration occurs in the floor slab and propagates from the piers and foundation to the ground. Here, the reference waveform at the bottom of the pier is used as the reference point unit pattern, and the vibration propagates from the bottom of each pier on the plane to the ground surface, and a method of calculating the combined value at the prediction point is considered, and the establishment of a prediction method is examined. bottom. In addition, we will report on the results of an attempt to predict the vibration propagation situation to the surroundings for a large vehicle test run and compare it with the actual measurement value. In addition, we examined the calculation procedure assuming traffic flow conditions in this model.

Restoration of saturated outputs from microchannel plate photomultiplier tubes in sub-microsecond single-pulse-current mode

Microchannel plate (MCP) photomultiplier tubes (PMTs) are frequently used in experimental diagnostics, where they are operated in single-pulse current measurement mode. However, considering the significant amplitude fluctuations in the measured signal, the resulting output signal from the MCP-PMT is inevitably distorted by gain saturation. Therefore, understanding the correlation between the MCP-PMT output signal and gain saturation is critical in assessing the extent of output signal distortion and determining the MCP-PMT saturation level. This knowledge allows for a more precise assessment of the input signal's features. In this paper, we present an experimental method for restoring the initial waveform from the saturated MCP-PMT signal. To correct the amplitude-drop caused by gain saturation, our technique involves calibrating the MCP-PMT's relative gain as a function of the accumulated output charge using a square-wave light source. We then applied this approach to restore a ∼500 ns saturated pulse from a double-layer 10 mm diameter MCP-PMT. The restored signal showed a deviation of less than 6% from the reference waveform, which validates the effectiveness of the technique.

Prediction of the internal structure of a lithium-ion battery using a single ultrasound wave response

This paper describes a means to predict the internal structure of a lithium-ion battery from the response of an ultrasonic pulse, using a genetic algorithm. Lithium-ion batteries are sealed components and the internal states of the cell such as charge, health, and presence of structural defects are difficult to measure. Ultrasonic inspection of lithium-ion batteries is a recent and growing area of research. Reflected and transmitted ultrasound pulses are proposed as a non-invasive means of gaining insights into the internal structure and changes within the closed body of a cell. However, the multiple layers present in a lithium-ion cell are problematic when attempting to interpret waveforms as many internal reflections superimpose. Attributing specific features of a cell to wave characteristics is challenging.In this work a genetic algorithm has been developed as a means to reverse engineer a single ultrasound wave response to predict the internal layered structure of a lithium-ion battery cell. A first randomised guess at the layered structure is made. A numerical wave propagation model is used to predict the ultrasound waveform associated with that structure. This waveform is then compared with a measured or reference waveform to establish its fitness. The layered structure is generationally mutated until the predicted waveforms converge on the reference signal. As this occurs the predicted layered body reveals insights into the cell structure under inspection.Initially, the algorithm was tested against an idealised model battery and its predicted waveform, giving a model-model verification. Further, experimental ultrasonic reflection signals were captured from small capacity lithium-ion cells. Estimations of layer structure predicted by the model were compared with CT-scans of the cells to assess performance. The genetic algorithm was found to be effective in converging the predicted wave response to the reference signal and creating accurate battery structures. It was shown that only part of the waveform was required to generate accurate predictions, which is helpful in avoiding parts of the signal contaminated by near field transducer effects.It was demonstrated that the genetic algorithm can predict material wave speed to 40–1100 m/s (3–29 %) accuracy when battery layer geometry is provided; and thicknesses to within approximately 0.2–7.5 μm (1–13 %) when material properties are provided. Providing the genetic algorithm with parameter constraints; either the layer topology and/or the material properties, substantially improved predictions to estimate the wave speeds on average to approximately ±50 m/s (3–4 %) and the layer thicknesses ±5 μm (7–8 %).This raises the possibility of the use of this approach to predict state of charge when the battery construction is known, or the presence of internal defects and damage to a known battery material composition.

Noncontact measurement of bolt axial force during tightening processes using scattered laser ultrasonic waves

This paper presents a new methodology for noncontact measurement of the axial force of bolts in their tightening processes using laser-generated ultrasound waves. This method employs ultrasound waves scattered in a bolt shaft to detect axial force changes, while most conventional ultrasonic methods use ultrasound waves propagating linearly along the bolt axis. The ultrasound waves in this study are generated by laser irradiation on the top surface of a bolt. Subsequently, they propagate deeply into the shaft and return towards the top of the bolt through complicated paths due to the multiple scattering in the bolt shaft. Finally, they are detected at the top surface using another laser and a speckle knife edge detector. With an examination based on the finite element analysis and verification experiments, it has been shown that the waveform of the scattered ultrasound shifts in time linearly with increasing the axial force. The time shifts were estimated using the cross-correlation analysis between the measured waveforms and the reference waveform with no axial force. This result demonstrates the feasibility of estimating the change in axial force during tightening processes once the relationship between the time shifts and axial force is obtained for the specific type of bolt to be used in products. Furthermore, the proposed technique does not require machining to flatten a bolt's head and the end, while conventional ultrasonic methods need the flattening procedures, enabling fast, cost-effective axial force measurement in mass production manufacturing processes.

Joint Design of Transmitting Waveform and Receiving Filter via Novel Riemannian Idea for DFRC System

Recently, the problem of target detection in noisy environments for the Dual-Functional Radar Communication (DFRC) integration system has been a hot topic. In this paper, to suppress the noise and further enhance the target detection performance, a novel manifold Riemannian Improved Armijo Search Conjugate Gradient algorithm (RIASCG) framework has been proposed which jointly optimizes the integrated transmitting waveform and receiving filter. Therein, the reference waveform is first designed to achieve excellent pattern matching of radar beamforming. Furthermore, to ensure the quality of system information transmission, the energy of multi-user interference (MUI) of communication signals is incorporated as the constraint. Additionally, the typical similarity constraint is introduced to ensure the transmitting waveform with a good ambiguity function. Finally, simulation results demonstrate that the designed waveform not only enhances the system’s target detection performance in noisy environments but also achieves a relatively good multi-user communication ability when compared with other prevalent waveforms.

Fully convolutional neural network and PPG signal for arterial blood pressure waveform estimation

Objective. The quality of the arterial blood pressure (ABP) waveform is crucial for predicting the value of blood pressure. The ABP waveform is predicted through experiments, and then Systolic blood pressure (SBP), Diastolic blood pressure, (DBP), and Mean arterial pressure (MAP) information are estimated from the ABP waveform. Approach. To ensure the quality of the predicted ABP waveform, this paper carefully designs the network structure, input signal, loss function, and structural parameters. A fully convolutional neural network (CNN) MultiResUNet3+ is used as the core architecture of ABP-MultiNet3+. In addition to performing Kalman filtering on the original photoplethysmogram (PPG) signal, its first-order derivative and second-order derivative signals are used as ABP-MultiNet3+ enter. The model’s loss function uses a combination of mean absolute error (MAE) and means square error (MSE) loss to ensure that the predicted ABP waveform matches the reference waveform. Main results. The proposed ABP-MultiNet3+ model was tested on the public MIMIC II databases, MAE of MAP, DBP, and SBP was 1.88 mmHg, 3.11 mmHg, and 4.45 mmHg, respectively, indicating a small model error. It experiment fully meets the standards of the AAMI standard and obtains level A in the DBP and MAP prediction standard test under the BHS standard. For SBP prediction, it obtains level B in the BHS standard test. Although it does not reach level A, it has a certain improvement compared with the existing methods. Significance. The results show that this algorithm can achieve sleeveless blood pressure estimation, which may enable mobile medical devices to continuously monitor blood pressure and greatly reduce the harm caused by Cardiovascular disease (CVD).

Basic study on calibration using waveform variation in space charge measurement by pulsed electroacoustic method

AbstractThe pulsed electroacoustic method determines the distribution of space charge in an insulation system by applying a pulse voltage and detecting the acoustic response. It estimates the location and magnitude of charges from time‐domain signals. For quantitative analysis, a bias voltage is applied to a specimen with no space charge, and the acoustic signal generated from the electrodes only is used as a reference waveform for calibration. However, a full‐scale, extra‐high voltage insulation system often already contains space charges in it. Therefore, a method of acquiring a reference signal under such a condition was studied. We studied methods to compare voltage variations and response signal variations. We proposed a method that measures the signal difference at different voltages. In addition, we proposed a method of correlating voltage and signal variations that may allo for more rapid signal acquisition. The feasibility was proved using an 11 mm‐thick mimic polyethylene specimen.

Hybrid modeling on reconstitution of continuous arterial blood pressure using finger photoplethysmography

The continuous estimation of arterial blood pressure (ABP) waveforms directly from single-channel photoplethysmography (PPG) signals will predictably change the way to monitor blood pressure in the future. This article proposed a new hybrid mathematical model for continuous blood pressure monitoring by investigating the relationship between the finger PPG signal and the radial ABP signal based on a public database. Considering potential damping factors and wave propagation/reflection in blood circulation, we combined the electrical network model with the tube-load model. The optimal range of model parameters was obtained through the system identification method to realize the individualized continuous blood pressure measurements. Compared with the invasive measurement, the hybrid model performed superior blood pressure estimation with high consistency. The estimated ABP waveforms correlated highly with the reference waveforms with an average correlation coefficient of 0.96. The mean absolute error/standard deviation of the estimated systolic blood pressure (SBP), mean arterial blood pressure (MAP), and diastolic blood pressure (DBP) were 3.0/4.4, 2.1/3.0 and 2.1/3.2 mmHg, respectively. The results met the requirements of the Association for the Advancement of Medical Instrumentation (AAMI). The hybrid model is expected to be embedded in small wearable devices to directly estimate the continuous blood pressure waveforms at the radial artery site through the PPG signals, pioneering the synchronous non-sensing monitoring on blood pressure and blood flow.

Embracing Channel Estimation in Multi-Packet Reception of ZigBee

As a low-power and low-cost wireless protocol, the promising ZigBee has been widely used in sensor networks and cyber-physical systems. Since ZigBee based networks usually adopt tree or cluster topology, the convergecast scenarios are common in which multiple transmitters send packets to one receiver, leading to the severe collision problem. The conventional ZigBee adopts carrier sense multiple access with collisions avoidance to avoid collisions, which introduces additional time/energy overhead. The state-of-the-art methods resolve collisions instead of avoidance, in which mZig decomposes a collision by the collision itself and reZig decodes a collision by comparing with reference waveforms. However, mZig falls into high decoding errors only exploiting the signal amplitudes while reZig incurs high computational complexity for waveform comparison. In this paper, we propose CmZig to embrace channel estimation in multiple-packet reception (MPR) of ZigBee, which effectively improves MPR via lightweight computing used for channel estimation and collision decomposition. First, CmZig enables accurate collision decomposition with low computation complexity, which uses the estimated channel parameters modeling both signal amplitude and phase. Second, CmZig adopts reference waveform comparison only for collisions without chip-level time offsets, instead of the complex machine learning based method. We implement CmZig on USRP-N210 and establish a six-node testbed.

Basic Study on Calibration using Waveform Variation in Space Charge Measurement by Pulsed Electroacoustic Method

The pulsed electroacoustic method determines the distribution of space charge in an insulation system by applying a pulse voltage and detecting the acoustic response. It estimates the location and magnitude of charges from time-domain signals. For quantitative analysis, a bias voltage is applied to a specimen with no space charge, and the acoustic signal generated from the electrodes only is used as a reference waveform for calibration. However, a full-scale, extra-high voltage insulation system often already contains space charges in it. Therefore, a method of acquiring a reference signal under such a condition was studied. We studied methods to compare voltage variations and response signal variations. We proposed a method that measures the signal difference at different voltages. In addition, we proposed a method of correlating voltage and signal variations that may allow for more rapid signal acquisition. The feasibility was proved using an 11 mm-thick mimic polyethylene specimen.

Transmission Design for Radar and Communication Spectrum Sharing Enhancement

In this work, we present a novel radar-communication spectrum sharing framework for transmission design. The design degrees of freedom (DoFs) under control are the radar transmit waveforms and the communication system code-book. The formulation of the spectrum sharing problem is stated as the maximization of the radar signal-to-interference-plus-noise ratio (SINR) under the constraints concerning the transmit energy, the radar similarity with a radar reference waveform, the communication system rate achievable. Compared with the traditional alternating convex transformation approach for the resulting non-convex problem, a novel algorithm is proposed based on the derived local design for radar waveform (LDFRW) to reduce the computational complexity. The numerical results show the merits of the proposed design.

Pulse Wave Analysis Method of Cardiovascular Parameters Extraction for Health Monitoring.

A pulse waveform is regarded as an information carrier of the cardiovascular system, which contains multiple interactive cardiovascular parameters reflecting physio-pathological states of bodies. Hence, multiple parameter analysis is increasingly meaningful to date but still cannot be easily achieved one by one due to the complex mapping between waveforms. This paper describes a new analysis method based on waveform recognition aimed for extracting multiple cardiovascular parameters to monitor public health. The objective of this new method is to deduce multiple cardiovascular parameters for a target pulse waveform based on waveform recognition to a most similar reference waveform in a given database or pattern library. The first part of the methodology includes building the sub-pattern libraries and training classifier. This provides a trained classifier and the sub-pattern library with reference pulse waveforms and known parameters. The second part is waveform analysis. The target waveform will be classified and output a state category being used to select the corresponding sub-pattern library with the same state. This will reduce subsequent recognition scope and computation costs. The mainstay of this new analysis method is improved dynamic time warping (DTW). This improved DTW and K-Nearest Neighbors (KNN) were applied to recognize the most similar waveform in the pattern library. Hence, cardiovascular parameters can be assigned accordingly from the most similar waveform in the pattern library. Four hundred and thirty eight (438) randomly selected pulse waveforms were tested to verify the effectiveness of this method. The results show that the classification accuracy is 96.35%. Using statistical analysis to compare the target sample waveforms and the recognized reference ones from within the pattern library, most correlation coefficients are beyond 0.99. Each set of cardiovascular parameters was assessed using the Bland-Altman plot. The extracted cardiovascular parameters are in strong agreement with the original verifying the effectiveness of this new approach. This new method using waveform recognition shows promising results that can directly extract multiple cardiovascular parameters from waveforms with high accuracy. This new approach is efficient and effective and is very promising for future continuous monitoring of cardiovascular health.

Control of Distributed Generation Using Non-Sinusoidal Pulse Width Modulation

The islanded mode is one of the connection modes of the grid distributed generation resources. In this study, a distributed generation resource is connected to linear and nonlinear loads via a three-phase inverter where a control method needing no current sensors or compensator elements is applied to the distribute generation system in the islanded mode. This control method has two main loops in each phase. The first loop controls the voltage control loops that adjust the three-phase point of common coupling, the amplitude of the non-sinusoidal reference waveform and the near-state pulse width modulation (NSPWM) method. The next loop compensatesthe harmonic compensator loop that calculates the voltage harmonics of the point of common coupling in each phase, and injects them to compensate the non-sinusoidal reference waveforms of each phase. The simulation results in MATLAB/SIMULINK show that this method can generate balanced three-phase sinusoidal voltage with an acceptable total harmonic distortion (THD) at the joint connection point.

An improved three phase cascaded multilevel inverter for maximum power point tracking application

A Three Phase Cascaded Multilevel (21 level) Inverter (3PMLI) is a superior alternative to medium-voltage inverter with intrinsic component redundancy. The 3PMLI achieves high quality input current and output voltage through a series connection of single-phase inverters. In case of applications like elevators, downhill conveyors and energy plants, regenerative issue is considered maximal due to bidirectional power flow. Hence, a 3PMLI fails in providing the required regenerative operation. In this paper, the Grey Wolf Optimisation - Fuzzy Logic Controller (GWO-FLC) with PI controller is used to control the Maximum Power Point (MPP) tracking of the MPPT. This method uses a GWO-FLC is designed to tune the membership function of FLC. The GWO-FLC with PI controller produces reference waveform for the level shifting (LS) method, which generates commutation signals for the boost converter. LS used in the study is Multicarrier Level Shifting - Pulse Width Modulation (MCLS-PWM) that generates the commutation signals for boost converter. A 21 levelled 3PMLI is used with a regenerative topology that increases the applicability of MLI. The regenerative 3PMLI is used to drive the Photo-Voltaic(PV)Maximum Power Point Tracking (MPPT) application. The mathematical modelling of PV MPPT application is carried out with Simulink. The coding is developed in very high-speed description language (VHDL) and implemented on Xilinx SPARTAN-III 3AN-XC3S400-FPGA processor. The proposed strategy is compared with existing fuzzy based Genetic Algorithm and GWO to prove its effectiveness. An extensive experimental analysis of the proposed technique takes place on benchmark datasets and the resultant outcomes are investigated with respect to distinct measures. The simulation results highlighted the enhanced performance of the proposed technique compared to existing techniques.

Power quality improvement in single-phase transformerless semi-quasi-Z-source inverters for off-grid photovoltaic systems

The transformerless single-phase semi-quasi-Z-source inverter (SqZSI) provides several advantages over classical PWM converters. Reduced or eliminated leakage current, high power density, and low cost are important features making this topology an attractive choice for PV micro-inverter applications. Two drawbacks of this topology are DC and second harmonic injection in the output AC port, which in some cases prevent the fulfillment of standard requirements. To alleviate this power quality issue, four novel harmonic mitigation algorithms based on PI and PR controllers are proposed, analyzed, and experimentally verified with the 90 W SqZSI in this paper. Moreover, a modified modulation reference waveform strategy is introduced. Consequently, the converter performance, in terms of total harmonic distortion (THDV) is achieved at about 1.27% under full power load. Also, in this paper, the non-ideal state-space model of the SqZSI with the effect of the equivalent series resistance of inductors is developed and the generation origin of DC and second harmonic component is analyzed based on the obtained model. The achieved results confirms the significant THD reduction by more than 75%, the DC component suppression, the second harmonic mitigation, and the power quality improvement.

Monopulse ladar: super-resolved 3D localization with Si-photonic serpentine optical phased arrays

We present an optical ranging and super-resolution object localization method, monopulse ladar, used to determine the angle of a point target in two dimensions to a few percent of an optical beam width from differential measurements of four just-resolved waveform-encoded beams while simultaneously providing target range via either coherent or incoherent coded waveform correlation. A common optical carrier is shifted by four GHz-scale tones, each modulated with distinct ranging waveforms, which when transmitted from a Si-photonic 2D wavelength-steered serpentine optical phased array (SOPA) aperture form an encoded rectangular beam cluster that propagates to and scatters from a distant point target. Superposed backscattered target returns from each beam are decoded by correlation with reference waveforms at the receiver. The angular position of the target along the two orthogonal axes is calculated from pairwise ratios of beam amplitudes, while target range is determined from the round-trip time delay of each beam as measured with a wideband correlation peak. The analysis of coherent and incoherent monopulse ladar architectures presented herein indicates that a 50-fold increase in angular resolution-to the tens of arcseconds level-of a point target located within a wide field of regard is achievable while maintaining cm-scale resolution-limited ranging using a single SOPA tile transmitter, with further improvement in angular resolution possible through arrayed tiling of SOPAs. Implementation of monopulse ladar with a SOPA aperture enables non-mechanically steered high-resolution 3D object localization in a compact, low-control complexity form factor.