Design Of Sensor Array Research Articles

Design of Graphene Pressure Sensor Array and its Ethernet-Based Demodulation System

Graphene pressure sensors have some problems, such as difficulty in sampling, difficulty in real-time remote monitoring and the limited sensor nodes in the system. A graphene pressure sensor array and its Ethernet-based demodulation system is proposed in this work, and the automatic detection of low-pressure is realized. This demodulation system can construct a LAN with multiple pressure sensor nodes, and monitor any sensor node in the LAN through the remote host computer. The self-made graphene pressure sensor array has high sensitivity (0.303 kPa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> in the range of less than 200 Pa and 0.038 kpa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> in the range of 200-1000 pa) and stability in the low-pressure range (< 1 kPa), which meets the detection requirements of low pressure. The demodulation system has the characteristics of high-precision sampling, high-speed transmission and remote real-time dynamic display. This work has certain application prospects in wearable electronic devices, electronic skin, intelligent human-computer interaction and engineering applications.

Modeling and Parallel Operation of Exchange-Biased Delta-E Effect Magnetometers for Sensor Arrays.

Recently, Delta-E effect magnetic field sensors based on exchange-biased magnetic multilayers have shown the potential of detecting low-frequency and small-amplitude magnetic fields. Their design is compatible with microelectromechanical system technology, potentially small, and therefore, suitable for arrays with a large number of sensor elements. In this study, we explore the prospects and limitations for improving the detection limit by averaging the output of sensor elements operated in parallel with a single oscillator and a single amplifier to avoid additional electronics and keep the setup compact. Measurements are performed on a two-element array of exchange-biased sensor elements to validate a signal and noise model. With the model, we estimate requirements and tolerances for sensor elements using larger . It is found that the intrinsic noise of the sensor elements can be considered uncorrelated, and the signal amplitude is improved if the resonance frequencies differ by less than approximately half the bandwidth of the resonators. Under these conditions, the averaging results in a maximum improvement in the detection limit by a factor of . A maximum exists, which depends on the read-out electronics and the sensor intrinsic noise. Overall, the results indicate that significant improvement in the limit of detection is possible, and a model is presented for optimizing the design of delta-E effect sensor arrays in the future.

Design of a MEMS sensor array for dam subsidence monitoring based on dual-sensor cooperative measurements

Design of a MEMS sensor array for dam subsidence monitoring based on dual-sensor cooperative measurements

Design and fabrication of effective gradient temperature sensor array based on bilayer SnO2/Pt for gas classification

Classification of different gases is important, and it is possible to use different gas sensors for this purpose. Electronic noses, for example, combine separated gas sensors into an array for detecting different gases. However, the use of separated sensors in an array suffers from being bulky, high-energy consumption and complex fabrication processes. Generally, gas sensing properties, including gas selectivity, of semiconductor gas sensors are strongly dependent on their working temperature. It is therefore feasible to use a single device composed of identical sensors arranged in a temperature gradient for classification of multiple gases. Herein, we introduce a design for simple fabrication of gas sensor array based on bilayer Pt/SnO2 for real-time monitoring and classification of multiple gases. The study includes design simulation of the sensor array to find an effective gradient temperature, fabrication of the sensors and test of their performance. The array, composed of five sensors, was fabricated on a glass substrate without the need of backside etching to reduce heat loss. A SnO2 thin film sensitized with Pt on top deposited by sputtering was used as sensing material. The sensor array was tested against different gases including ethanol, methanol, isopropanol, acetone, ammonia, and hydrogen. Radar plots and principal component analysis were used to visualize the distinction of the tested gases and to enable effective classification.

Design, development and testing of digital MEMS pressure sensor array for full-scale vibroacoustic measurements

This manuscript addresses design, development, and application of micro-electro-mechanical systems (MEMS) based digital pressure sensor array for vibroacoustic measurements. These vibroacoustic measurements were conducted on a A320 type single aisle aircraft demonstrator subjected to broadband as well as tonal excitations. Cabin noise levels were measured with both condenser microphones as well as digital MEMS pressure sensor array. The measured cabin noise shows strong qualitative as well as quantitative agreement between both type of measurement devises for full scale cabin noise measurements inside an aircraft demonstrator. The observed strong agreement is valid for both single wall (fuselage with thermal insulation) and double wall (fuselage with thermal insulation and trim panel) cabin noise measurements. Such strong agreement within 1.0 dB tolerance is significantly motivating for further development of reliable but low-cost MEMS based measurement devises and corresponding efficient data post-processing algorithms for full scale vibroacoustic measurements in general. Additionally, it is also demonstrated that the large number of MEMS based digital pressure sensors can be used in areas where the physical space constraints are high. This demonstration shows strong potential to derive additional vibroacoustic indicator for the development and the testing of future noise control solutions in a non-traditional way.

Sensor Array Complexity and Analytical Capability

Introduction Chemical sensors are generally associated with tasks involving detection of chemical stimuli while conventional analytical laboratory instruments are associated with analysis of chemical mixtures. While sensing tasks may not necessarily be perceived as involving chemical mixture analysis and evaluated as such, there is always an underlying analytical context in any sensing problem. This context becomes progressively more important as the complexity of chemical environment in which the sensing task is to be conducted increases, through both the number of potential intereferents as well as uncertainty regarding the composition of the chemical background.Design of individual sensors can be reasonably predicated on maximizing the sensitivity and selectivity of a narrowly-scoped chemical stimulus against expected backgrounds. However, as one may expect, design considerations can become significantly more complicated for systems based on sensor arrays. Arrays consisting of sensors that exhibit diverse, partially-selective response to a wide range of chemical stimuli allow, in theory, selective detection of a range of chemical stimuli against more complex backgrounds. [1] This is generally supported by analogy to biological olfaction as well as experimental work over the past few decades. Intuitively, a clear consequence of moving towards applications involving more complex and uncertain sensing tasks is a requirement that the system become less “sensor-like” and more “instrument-like.” A significant challenge in sensor array design has been that these concepts are not well-understood in a quantitative and device-agnostic fashion, making it difficult appropriately match sensor array and sensing task complexity in a predictable and systematic fashion. This presentation will discuss how analytical capabilities can be characterized on a continuum between simple sensor arrays and classical analytical instruments and the implications for sensor array design and selection. Approach Sensor array capability for determining composition of fixed, finite domains of independent chemical stimuli can be expressed and predicted using information-theoretic measures and knowledge of individual chemical response functions for each chemical stimulus/sensor pair. [2-4] Moving towards expression of more general-purpose analytical capability (i.e. dynamic, high-dimensional domains of independent chemical stimuli) requires a shift from consideration of the span of specific chemical stimuli to one of the span of molecular parameters probed by the sensor technology. Sensor array capability for addressing generalized chemical analysis problems can then be expressed in terms of the adjacency in molecular parameter space induced by the underlying response mechanism of a sensor technology and the manner in which specific sensor array configurations induce particular array sensitivities across this same domain of molecular parameters. Hypothetical sensor systems based on optical detection and chemisorption are used to illustrate these concepts. In particular, this framework allows consideration of the manner in which sensor arrays and laboratory instruments occupy a continuum of complexity with which they interact with the chemical environment. Conclusions This work demonstrates the value in developing improved first-principles models of sensor response grounded in molecular parameters rather than specific chemical stimuli. Such an understanding allows expression and prediction of the extent to which a sensor array offers “instrument like” general purpose capability as opposed to narrowly scoped sensing tasks. The complexity of a given sensor technology’s interaction with the chemical environment ultimately provides a limit to the complexity of chemical sensing tasks that are addressable by sensor arrays based on this technology. Considering these aspects of chemical sensor array design allows more reliable selection and design of sensor arrays for complex, real-world applications.

The Complexity of Analytical Tasks: A Driving Force for Sensor Array Design

Introduction Analytical tasks, the detection goals and scoping of quantitative measurements, are a foundational consideration for the design of chemical sensor arrays. Often sensor arrays are expected to support a variety of possible tasks which are only vaguely defined by both the end user and array designer. Nonetheless, the expedient choices made by or forced upon array designers and fabricators can significantly impact the analytical tasks that could be supported by an array. Analytical tasks may be defined as boundaries in an abstract space defining chemically and practically relevant quantities that are to be measured; chemical sensor and instrument responses may be defined in related spaces specific to their physics. Intelligently finding a mapping between these two abstract spaces defines our problem and informs the impact of analytical tasks upon sensor array design while avoiding the “black box” problems of popular machine learning approaches. This presentation details recent work at NRL that probes the meaning and impact of analytical tasks on chemical sensor array design through general, device agnostic figures of merit developed via techniques originating in statistical mechanics, information theory, information retrieval, and theoretical computer science. Approach Multiple theoretical approaches are explored to determine and measure the impact of analytical task on chemical sensor array design. To begin, we use Ising model-like descriptions of binary sensor responses first described in a biological context by Murugan et. al. [1-3] and subsequently developed by us for chemical sensing with environmental interferents. Analytical tasks are then scoped as molecular and concentration identification against an unknown chemical background. On this framework, we explore the capabilities of a variety of approaches towards assessing the impact of analytical task on sensor array design.The first set of approaches originate in information theory and we consider the mutual information and Kullback-Leibler divergences between different sensor array configurations considered over probability distributions defining the likelihood of that sensor array needing to perform different analytical tasks. Platform-agnostic figures of merit are derived and used to show the impact of analytical tasks on sensor array design.Next, Van Riijsbergen and Melucci [4,5] have developed and elaborated upon an approach to representing and searching information in Hilbert spaces using operator theoretic methods reminiscent to those used in quantum mechanical calculations. By transferring our probabilistic sensor array models to a Hilbert space, we are able to perform similar searches against sensor arrays and by operator methods to ask logical questions of the sensor array using operators that encode analytical tasks and specific exigencies like comparisons to the effectiveness of the array for other analytical tasks.Finally, Almagor et. al. [6-9] have recently developed a finite state machine approach for formally describing the complexity of sensing tasks within formal languages. We attempt to map our binary chemical sensor array model to this methodology and to describe the formal complexity of this toy model for chemical sensing. Analytical tasks are input as restrictions on available formal words in the finite state language. Conclusions Using a simple statistical mechanical model for a chemical sensor array with background interferents, we have been able to probe multiple approaches to quantifying the impact of analytical tasks on the design and relevance of a sensor array for a set of chemical detection problems. Importantly, these approaches avoid drawbacks associated with more empirical, machine learning-based approaches, enabling a more clear understanding of the chemical landscape and how chemical sensor array design interacts with it. Our investigation has explored ways to construct figures of merit for specific families of analytical tasks using methodologies as diverse as information theory, Hilbert space search methods, and complexity techniques for automata-defined sensing.

Excitation wavelength as additional dimension in cross-reactive sensor arrays

Cross-reactive sensor arrays have powerful abilities in distinguishing multiple analytes. The larger the effective data volume is, the better the detection performance is. However, current collected data volume depends heavily on the amount of sensing materials involved. It is data-inefficient for each material and causes heavy workload to prepare materials. Herein, by introducing the dimension of excitation wavelength, we report a cross-reactive sensor array by using only one fluorescent material (β-cyclodextrin-modified quantum dots, QD-β-CD). The newly added dimension is demonstrated by collecting emission signals under four excitation wavelengths. Through machine learning algorithms, the cross-reactive sensor array can be used for the detection of single nitrophenol (NP) isomer (e.g. a superior detectability with a classification accuracy of 94.9 % for 0.01 μM p-nitrophenol), and concurrent quantitative analysis of complex binary/ternary NP mixtures in environment analysis. Our results indicate that the additional dimension of excitation wavelength can provide an effective way to increase the differences of multiple analytes in the design of cross-reactive sensor array. The idea of adding an extra dimension can be generally applicable for the fields of multidimensional information collection.

Ceramic multilayer technology as a platform for miniaturized sensor arrays for water analysis

Abstract. Ion-selective electrodes (ISEs) have been proven particularly useful in water analysis. They are usually used as single-rod measuring chains in different designs, which are manufactured using precision mechanical manufacturing and assembling technologies. The paper describes a microsystem technology approach for the fabrication of miniaturized electrochemical sensors. The ceramic HTCC (high-temperature co-fired ceramic) and LTCC (low-temperature co-fired ceramic) multilayer technology enables suitable processes for the manufacturing of robust and miniaturized sensor arrays with a high functional density. Design, manufacture, and electrochemical performance of the novel ceramic multilayer-based sensor array are presented in the paper using various examples. An adapted material and process development was carried out for the sensitive functional films. Special thick-film pastes for the detection of the pH value as well as NH4+, K+, Ca2+, and Cu2+ ion concentrations in aqueous solutions were developed. Ion-sensitive thick-film membranes were deposited on a ceramic multilayer sensor platform by means of screen-printing. All ISEs, integrated in the sensor array, showed suitable electrochemical performances including a very quick response (several seconds) combined with a high sensitivity (exhibiting Nernstian behaviour) in the tested measuring range. The obtained sensitivities were around 57 mVper decade: for the pH sensor, 30 mVper decade for calcium, 53 mVper decade for potassium, and 57 mVper decade for ammonium. Depending on the application, different sensitive electrodes on the ceramic sensor array can be combined as required.

Design and Application of MEMS-Based Hall Sensor Array for Magnetic Field Mapping

A magnetic field measurement system based on an array of Hall sensors is proposed. The sensors are fabricated using conventional microelectromechanical systems (MEMS) techniques and consist of a P-type silicon substrate, a silicon dioxide isolation layer, a phosphide-doped cross-shaped detection zone, and gold signal leads. When placed within a magnetic field, the interaction between the local magnetic field produced by the working current and the external magnetic field generates a measurable Hall voltage from which the strength of the external magnetic field is then derived. Four Hall sensors are fabricated incorporating cross-shaped detection zones with an identical aspect ratio (2.625) but different sizes (S, M, L, and XL). For a given working current, the sensitivities and response times of the four devices are found to be almost the same. However, the offset voltage increases with the increasing size of the detection zone. A 3 × 3 array of sensors is assembled into a 3D-printed frame and used to determine the magnetic field distributions of a single magnet and a group of three magnets, respectively. The results show that the constructed 2D magnetic field contour maps accurately reproduce both the locations of the individual magnets and the distributions of the magnetic fields around them.

Design and Characterisation of a Non-Contact Flexible Sensor Array for Electric Potential Imaging Applications

Capacitive non-contact imaging of electric fields and potentials with micro-metre resolution can provide relevant insights into material characterisation, structural analysis, electrostatic charge imaging and bio-sensing applications. However, scanning electric potential microscopes have been confined to rigid and single-probe devices, making them slow, prone to mechanical damage and complex to fabricate. In this work, we present the design and characterisation of a novel 5-element flexible array of electric potential probes with spatial resolution down to 20μm to speed up the scanning time. This was achieved by combining flexible thin-film probes for active guarding and shielding with state-of-the art discrete conditioning circuits. The potential of this approach is showcased by using the fabricated array to image latent fingerprints deposited on an insulating surface by contact electrification, obtain the surface topography of conductive samples and to visualise local dielectric variations.

Nanoengineering Approaches Toward Artificial Nose.

Significant scientific efforts have been made to mimic and potentially supersede the mammalian nose using artificial noses based on arrays of individual cross-sensitive gas sensors over the past couple decades. To this end, thousands of research articles have been published regarding the design of gas sensor arrays to function as artificial noses. Nanoengineered materials possessing high surface area for enhanced reaction kinetics and uniquely tunable optical, electronic, and optoelectronic properties have been extensively used as gas sensing materials in single gas sensors and sensor arrays. Therefore, nanoengineered materials address some of the shortcomings in sensitivity and selectivity inherent in microscale and macroscale materials for chemical sensors. In this article, the fundamental gas sensing mechanisms are briefly reviewed for each material class and sensing modality (electrical, optical, optoelectronic), followed by a survey and review of the various strategies for engineering or functionalizing these nanomaterials to improve their gas sensing selectivity, sensitivity and other measures of gas sensing performance. Specifically, one major focus of this review is on nanoscale materials and nanoengineering approaches for semiconducting metal oxides, transition metal dichalcogenides, carbonaceous nanomaterials, conducting polymers, and others as used in single gas sensors or sensor arrays for electrical sensing modality. Additionally, this review discusses the various nano-enabled techniques and materials of optical gas detection modality, including photonic crystals, surface plasmonic sensing, and nanoscale waveguides. Strategies for improving or tuning the sensitivity and selectivity of materials toward different gases are given priority due to the importance of having cross-sensitivity and selectivity toward various analytes in designing an effective artificial nose. Furthermore, optoelectrical sensing, which has to date not served as a common sensing modality, is also reviewed to highlight potential research directions. We close with some perspective on the future development of artificial noses which utilize optical and electrical sensing modalities, with additional focus on the less researched optoelectronic sensing modality.

Integrated sensing array of the perovskite-type LnFeO3 (Ln˭La, Pr, Nd, Sm) to discriminate detection of volatile sulfur compounds

Distinguishing toxic gases among the various volatile sulfur compounds (VSCs) is of significant practical value for atmospheric and environmental pollution monitoring, industrial monitoring, and even for medical diagnostics (where VSCs are indicators of diseases). The particular challenge lies in the detection and discrimination of sulfur-containing gases such as dimethyl disulfide (DMDS), methyl sulfide (DMS), hydrogen sulfide (H2S), and carbon disulfide (CS2) is of value. Herein, single-phase perovskite-type LnFeO3 nanoparticles were prepared by the citrate sol-gel method. Their gas sensing characteristics regard to the four typical VSCs were investigated. We found that the gas response of the p-type semiconductor LnFeO3 gas sensors to the four typical VSCs are significantly different. In addition, the sensors offer high performance, good tolerance to environmental changes and long-term stability for detecting VSCs gas at an operating temperature of 210 °C. A new design of sensor array was realized by integrating a series of LnFeO3 materials, which revealed excellent recognition ability for various VSCs, showing promise for real time monitoring.

Design of electrochemical sensor array utilizing metal materials and applications in sugar content analysis from mixtures

ABSTRACT In this paper, an electrochemical sensor array utilizing metal materials was designed, and its applications in sugar content analysis from mixtures were conducted. The system adopts the conventional three-electrode system. Cyclic Voltammetry (CV) and Amperometric i-t Curve (i-t) were utilized as testing methods. The curve of the relationship between current and time could be obtained by i-t scanning. The relationship between the sugar concentration and the current density of the sensor was developed. The data was analyzed using multiple linear regression (MLR). The sugar mixtures were automatically measured by using this instrument. CV and i-t methods were utilized to carry out the experiments. Different scan rates CV results showed that it was a typical diffusion controlled electrochemical process. Different sugars CV results showed that different electrodes for CV experiments with different sugars produced different anode peak potential and current. Control experiments showed that neither Na2CO3 nor NaCl had any effect on the experimental results. The developed system has good stability and repeatability. I-t fitting results indicated that there was a good linear relationship between system responses and sugar concentrations. The linear range was between 0.14 mM and 4.76 mM. A python-based MLR model was developed for sugar content determination. Results were obtained by solving the system of equations, indicating that this method presented content determination abilities for sugar mixtures. The method proposed in this paper had the advantages of easy operation, low cost, rapid analysis, and low detection limit. It provided a new idea for sugar quantitative determination in solution.

Development of circuit solution and design of capacitive pressure sensor array for applied robotics

This paper presents development of pressure sensor array with capacitance-type unit sensors, with scalable number of cells. Different assemblies of unit pressure sensors and their arrays were considered, their characteristics and fabrication methods were investigated. The structure of primary pressure transducer (PPT) array was presented; its operating principle of array was illustrated, calculated reference ratios were derived. The interface circuit, allowing to transform the changes in the primary transducer capacitance into voltage level variations, was proposed. A prototype sensor was implemented; the dependency of output signal power from the applied force was empirically obtained. In the range under 30 N it exhibited a linear pattern. The sensitivity of the array cells to the applied pressure is in the range 134.56..160.35. The measured drift of the output signals from the array cells after 10,000 loading cycles was 1.39%. For developed prototype of the pressure sensor array, based on the experimental data, the average signal-to-noise ratio over the cells was calculated, and equaled 63.47 dB. The proposed prototype was fabricated of easily available materials. It is relatively inexpensive and requires no fine-tuning of each individual cell. Capacitance-type operation type, compared to piezoresistive one, ensures greater stability of the output signal. The scalability and adjustability of cell parameters are achieved with layered sensor structure. The pressure sensor array, presented in this paper, can be utilized in various robotic systems.

A Paper-Based Flexible Tactile Sensor Array for Low-Cost Wearable Human Health Monitoring

This paper presents the design, fabrication, and characterization results of a paper-based, low-cost, easy-to-use, comfortable and wearable tactile sensor array for human health monitoring applications. Paper substrate and spray-deposited metallic electrodes and traces are employed to achieve a low fabrication cost. Capacitive sensing scheme employing a deformable triangular PDMS sensing membrane is chosen due to its high sensitivity and zero DC power dissipation. Trade-offs among different sensor array designs are investigated to achieve an optimal design, which consists of a $1\times 5$ sensor array occupying an area of 10 mm $\times10$ mm. Each sensor in the array achieves a nominal capacitance value and sensitivity of approximately 1 pF and 30 fF/mmHg, respectively. Fabricated sensor array can be comfortably attached to an individual's temporal region and ankle area to monitor real-time blood pressure (BP) pulse waveform with high fidelity, from which heart rate and heart rate variability information can be accurately obtained. In addition, the prototype sensor array demonstrates its capability of detecting atrial fibrillation (AFib) from BP pulse waveform measured from an AFib patient. [2020-0179]

Side-coupled liquid sensor and its array with magneto-optical photonic crystal.

In this paper, a side-coupled liquid sensor and its array based on magneto-optical photonic crystal are proposed. The sensitivity and quality factor of a single magneto-optical photonic crystal sensor are 0.492 mm/RIU and 181,760, respectively. After arraying, the sensitivity of the single microcavity sensor can reach from 0.1 to 0.35 mm/RIU, and the corresponding quality factor can reach from 5×104 to 7×104. Moreover, the structure has good robustness. This work will provide reference for the design of high-performance photonic crystal microcavity sensor arrays.

Design of Pressure Sensor Arrays to Assess Electrode Contact Pressure During In Vivo Recordings in the Gut.

The gastrointestinal (GI) tract is in part controlled by slow wave electrical activity. Recordings of slow waves with high-resolution (HR) electrode arrays are used to characterize normal and abnormal conduction pathways. Improving the quality of these electrical recordings is important for developing a better understanding of abnormal activity. Contact pressure is one factor that can affect the quality of electrical recordings. We compared the performance of two pressure sensing devices for measuring HR electrode array contact pressure. A Velostat-based sensor array was custom designed and built in a 4 × 2 conguration (area: 30 mm2 per sensor) to be integrated into electrical recordings. Commercially available FlexiForce A201 sensors were used to compare to the Velostat-based sensors. Benchtop testing of these sensors was performed; the error of the Velostat-based sensors (14-31%) was better than that of the FlexiForce sensors (20-49%) within a range of 2666-6666 Pa. The Velostat-based sensors were also more repeatable than the FlexiForce sensors over the same pressure range. Simultaneous pressure and slow wave recordings were performed in vivo on a rabbit small intestine. The Velostat-based sensors were able to resolve spatiotemporal changes in contact pressure in the range of 0-10 000 Pa.

Parametric Reconstruction of Multiple Line Currents Based on Magnetic Sensor Array

Current measurement is of great importance for the state monitoring and parameter identification in a power grid. This article proposed a contactless magnetic-based sensor array method for the acquisition of line current parameters, aiming at the measurement for arbitrary line currents. The inverse problem between the line current with arbitrary parameters and the magnetic field was introduced. Due to the nonlinearity of the inverse problem, a comprehensive algorithm consisting of metaheuristic algorithms and interior point method was employed. The influences of structural parameters on the calculation accuracy have been explicitly studied, indicating the optimal sensor array design parameters concerning the number of sensors, the distance between adjacent sensors, and the shape of sensor array. The sensor array was implemented by utilizing the dual-axial tunneling magnetoresistive (TMR) magnetic-field measurement device. In terms of the 2-D magnetic-field measurement results for two currents with all parameters unknown, the current magnitude error was 0.6%, proving the effectiveness of the comprehensive algorithm together with the annular sensor array. The proposed method for current measurement gives a promising solution for various line current measurement requirements in the power grid.

MIMO Radar Array Configuration with Enhanced Degrees of Freedom and Increased Array Aperture

This paper presents a new antenna array design approach for multiple-input multiple-output (MIMO) radar. The geometry exhibits increased degrees of freedom (DOFs) with precise antenna locations for direction-of-arrival (DOA) estimation of sources. The enhancement is realized by using the method of sum coarray of the difference coarray (SCDC). By effectively increasing the inter-element spacing of the transmitting array, a larger hole-free SCDC uniform linear array (ULA) is obtained. This increment provides more DOFs and extended virtual array aperture (VAA) for intended geometry. The transmitting and receiving sensor positions are based on the maximum inter-element spacing constraint (MISC) principle. The MISC composition involves three sparse ULAs with two separate antennas placed appropriately. The mathematical expressions are presented to validate the designed model. Moreover, arbitrary and optimized antenna scenarios for the transmitter and receiver are investigated in terms of DOFs and VAA. The advantages of the proposed configuration are demonstrated by conducting rigorous Monte Carlo simulations. The experimental results of DOFs, VAA, number of resolvable sources, Cram $$\acute{\hbox {e}}$$ r–Rao bound performance, detection, and resolution ability reveal that the proposed sensor array design approach is suitable for MIMO radar which is also capable of estimating the DOAs of multiple sources efficiently in underdetermined scenarios.