Double Difference Research Articles

Driving green innovation: assessing the impact of environmental tax policies and green finance on heavily polluting industries

Purpose The purpose of this paper assess the impact of the green finance pilot reform on corporate green innovation, leveraging the establishment of the China green finance pilot reform in 2018 as a quasi-natural experiment. Design/methodology/approach This study investigates the effects of environmental policies on green innovation, utilising a substantial data set from Chinese A-share listed firms over the 2015–2019 period. Employing both double and triple difference models, it focuses on how tax reforms influence green patent filings among these firms. Findings The study confirms that environmental tax policies and green finance initiatives significantly boost green patent filings in pollution-intensive industries. Findings from the regression analysis show robust positive effects from these policies, supporting the idea that stringent environmental regulations can spur innovation by offsetting regulatory costs. Financial health indicators like asset logs and return on assets positively correlated with innovation, emphasising the importance of financial stability. In addition, increased RandD spending is linked to enhanced green innovation, highlighting that financial investment in research is crucial for overcoming innovation barriers. These insights are crucial for shaping policies that integrate sustainability into corporate practices. Originality/value This research contributes to the literature by highlighting traditional views on the economic burden of environmental taxes and demonstrating their role as significant drivers of innovation. It deepens insights into strategically optimising fiscal tools to promote environmentally sustainable economic activities. In addition, it offers a practical framework for policymakers to improve ecological outcomes through effective fiscal strategies.

Impact of LEO configuration on GPS precise orbit determination with un-differenced ambiguity resolution

Un-differenced (UD) ambiguity resolution (AR) is widely applied since it can avoid wrong-fixing and fix the most of ambiguities. However, in the precise orbit determination (POD) solution using ground network only, the accuracy of float estimates is not sufficient for a direct UD AR, and thus double-differenced (DD) AR must be conducted first. It is demonstrated that integrating low-Earth orbit (LEO) satellites improves the accuracy of ambiguity-float solutions and consequently the improved ambiguity estimates enable successful UD AR. With more and more LEO satellites receiving Global Positioning System (GPS) observations, it is important to investigate the effect of different LEO configurations for LEO-augmented GPS UD AR. In this study, about 100 stations of the International GNSS Service (IGS), and eight LEO satellites with five orbital configurations, including two GRACE-FO, three SWARM, two SENTINEL-3, and one SENTINEL-6 satellites, are used for integrated processing of LEO satellites and ground network. The influence of different numbers of LEO satellites and orbital configurations on the performance of UD POD is investigated by analyzing the POD results of the ground network together with 35 different LEO-satellite schemes. We demonstrate that the performance of POD, in terms of GPS orbit accuracy and unsuccessful fixing in the UD AR solution, depends on the accuracy of float estimates. The number of unsuccessful fixings can be reduced by the increasing number of LEO satellites and orbital configurations. Moreover, including LEO satellites from more orbital configurations is more efficient for a given number of LEO satellites.

The Impact of “Smart City” Pilot Construction on China’s Export Product Quality

Based on the double difference (DID) method, this study examines the impact of "smart city" pilot policies on the quality of export products in Chinese cities. Using data from three batches of smart city pilot cities from 2012 to 2014, the results show that smart city construction significantly improves the quality of export products in Chinese cities. It is found that smart city construction achieves a positive impact on export product quality through the paths of promoting technological innovation, upgrading informatization and optimizing resource allocation. In addition, the results of the heterogeneity analysis show that this policy effect is more significant in cities with a developed economy and a higher degree of openness to the outside world. The research in this paper provides empirical support for the formulation of smart city policies and offers policy suggestions for enhancing the export competitiveness of cities.

Green Finance, Economic Policy Uncertainty, and Corporate ESG Performance

Given the increasing prevalence of global warming and the frequent occurrence of extreme weather events and other challenges, countries are increasingly recognizing the importance of green and sustainable development. This paper uses the multi-period double difference and PSM-DID method to test the impact of green finance policies on the ESG performance of Chinese listed companies. Research has shown that implementing pilot zone policies can improve corporate ESG performance, especially for enterprises with low business reputations, fierce industry competition, severe information asymmetry, and state-owned attributes. The GFPZ policy drives companies to improve their ESG performance through two paths: promoting environmental innovation and strengthening restrictions on corporate financing. In addition, the increase in economic policy uncertainty hinders the positive impact of GFPZ policies on improving corporate ESG performance. This study enriches the existing micro-research on green finance policies from the perspective of enterprises. It provides empirical evidence and research insights to support the further improvement of pilot zone policies, the promotion of green sustainable development, and the improvement of corporate ESG performance.

Impact of improved cassava cultivars on income generation and food security of women farmers in Mkuranga district, Tanzania

PurposeThe study was conducted to investigate the impact of improved cassava cultivars on income generation and food security status of women farmers in Tanzania.Design/methodology/approachData were collected from 300 respondents (150 with improved cassava cultivars and 150 without) who were selected using purposive and random sampling techniques. Double Difference, Descriptive Statistics were the analytical tools. The Cost-of-Calorie Index was used to measure food security status of the respondents.FindingsResults show that Double Difference estimates indicated that the annual income of the women farmers with improved cassava cultivars increased by TZS 143,495.20 which was higher than that of the women farmers without improved cassava cultivars which increased by only TZS 58,500. There was a positive impact on income as a result of using the improved cassava cultivars. The Cost-of-Calorie Index showed that the food security line per adult equivalent per month was TZS 2,743.81 and TZS 2,076.69 for farmers with and without improved cassava cultivars respectively. About 66% of the women farmers with improved cassava cultivars and 33% of the women farmers without improved cassava cultivars were food secure. Policies should be formulated to encourage women farmers to adopt and sustain the use of improved cultivars of cassava.Research limitations/implicationsThe research may be limited by its scope and generalizability, as it focuses on a specific geographic area (Mkuranga District) and demographic group (women farmers).Social implicationsThe study shed light on the role of agricultural interventions in empowering women economically and enhancing their food security, potentially leading to improved social status and decision-making power within their households and communities.Originality/valueThe study contributes to the existing body of knowledge by emphasizing the benefits for women farmers when using improved cassava cultivars for income generation and food sufficiency.

The Effect of Medial Circumflex Artery Variation on the Success Rate of Gracilis Flap Procedures: A Systematic Review.

This systematic review examines the impact of anatomical variations in the medial circumflex artery (MCA) on the outcomes of gracilis flap procedures in reconstructive surgery. Incorporating 16 studies, this review analyzes how different MCA variants influence the success rates of these procedures. Findings highlight critical MCA variations, including cases of split and double pedicles and differences in pedicle length and branching patterns, which can complicate flap harvesting and vascular anastomosis. The studies consistently underscore the need for precise preoperative imaging and intraoperative adaptability to manage these anatomical differences effectively. Notably, variants with shorter or branched pedicles present higher risks of partial flap loss and complications, particularly in autologous breast reconstruction and lower extremity repairs. The findings support the adoption of advanced imaging protocols, such as high-resolution Doppler and CT angiography, to enable detailed vascular mapping. Interdisciplinary collaboration among anatomists, radiologists, and surgeons is essential for developing comprehensive strategies tailored to individual anatomical landscapes, optimizing both the success and viability of gracilis flaps. The review emphasizes that understanding MCA variability is crucial for enhancing surgical precision and improving patient outcomes. Standardizing preoperative assessment protocols and exploring alternative flap techniques may mitigate risks associated with MCA variations, advancing the field of reconstructive surgery.

Can Open Government Data Improve City Green Land-Use Efficiency? Evidence from China

This study adopted the double difference method to study the effect of open government data (OGD) on city green land-use efficiency (CGLUE). It was found that opening government data had a significant promotional effect on CGLUE, and a number of robustness tests were the foundation for this finding. A mechanism analysis demonstrated that two key avenues via which government data openness can promote CGLUE are raising public awareness of environmental issues and strengthening urban green innovation potential. A heterogeneity analysis found that the effect of government data openness on CGLUE was more obvious in eastern cities, cities with higher levels of digital finance, and non-resource-based cities. In addition, open government data also reduced urban carbon emissions while improving CGLUE, contributing to China’s “double carbon” goal.

The Effects of Big Data Regulations on Industrial Modernization in Resource-Based Cities: A Semi-Natural Study Using a State-Level Big Data Coordination Zone

As a core component of the digital economy, big data provides resource-based cities with a new impetus for upgrading their industrial structures. This paper employs a double difference method with panel data from 86 resource cities in China from 2009 to 2020 in order to investigate the effects of big data policies on resource cities' upgrading of their industrial structures objectively. Quasi-control groups are the quasi-natural trials of two batches of 19 resource cities in national big data comprehensive experimental zones. The empirical results demonstrate that the nationwide comprehensive experimental zone for big data exerts a considerable influence on the industrial upgrading of resource-based cities. This conclusion remains robust even after putting it through a series of tests, including the consolidation test and the stability test. Ultimately, this study offers a novel approach to catalyzing industrial upgrading in a big data context, shedding light on crucial issues such as economic instability in resource-based cities.

Assessing the utility of low-emission pilot policies for facilitating pollution reduction and carbon mitigation: An empirical investigation using multi-temporal double difference analysis

Collaborative governance for pollution reduction and carbon mitigation can effectively resist the pressure brought about by ecological and environmental changes while reducing policy costs. To explore the “win-win” path of pollution reduction and carbon mitigation,” based on panel data from 286 cities in China from 2000 to 2021, this study regards the low-carbon city pilot policy (LCCP) as a quasi-natural experiment and explores its impact on urban carbon emissions and pm2.5 concentration. Multiple testing methods, including multi-temporal double difference, spatial autocorrelation, local cold and hot spot analysis, kernel density analysis, standard deviation ellipse, spatial Durbin model, and PSM-DID, were used to verify the credibility and scientificity of the research results. The results showed that (1) LCCP had a direct effect on reducing pollution and carbon emissions, reducing co2 emissions by 3% and pm2.5 by 2.9%, with a synergistic effect of 20.2%; (2) the synergistic effect of LCCP on pollution and carbon reduction was indirectly achieved through green finance, green technological innovation, and green transportation, with impacts of 3.6%, 5.5%, and 2.4% in eastern, central, and non-resource based cities, respectively; and (3) the spillover effect coefficient of LCCP on carbon emission reduction in surrounding cities was −0.040 and that on pm2.5 concentration was −1.232, which are significant at the 10% and 1% levels, respectively.

A novel recursive sub-tensor hyperspectral compressive sensing of plant leaves based on multiple arbitrary-shape regions of interest

Plant hyperspectral images (HSIs) contain valuable information for agricultural disaster prediction, biomass estimation, and other applications. However, they also include a lot of irrelevant background information, which wastes storage resources. In this paper, we propose a novel recursive sub-tensor hyperspectral compressive sensing method for plant leaves. This method uses recursive sub-tensor compressive sensing to compress and reconstruct each arbitrary-shape leaf region, discarding a large amount of background information to achieve the best possible reconstruction performance of the leaf region and significantly reduce storage space. The proposed method involves several key steps. Firstly, the optimal band is determined using the spatial spectral decorrelation criterion, and its corresponding mask image is used to extract the leaf regions from the background. Secondly, the recursive maximum inscribed rectangle algorithm is applied to obtain rectangular sub-tensors of leaves recursively. Each sub-tensor is then individually compressed and reconstructed. Finally, all sub-tensors can be reconstructed to form complete leaf HSIs without background information. Experimental results demonstrate that the proposed method achieves superior image reconstruction quality at extremely low sampling rates compared to other methods. The proposed method can improve average Peak Signal-to-Noise Ratio (PSNR) values by about 3.04% and 0.74% compared to Tensor Compressive Sensing (TCS) at the sampling rate of 2%. In the spectral domain, the proposed method can achieve significantly smaller Spectral Angle Mapper (SAM) values and relatively lower spectral indices errors for Double Difference, Triangular Vegetation Index, Leaf Chlorophyll Index, and Modified Normalized Difference 680 than those of TCS. Therefore, the proposed method achieves better compression performance for reconstructed plant leaf HSIs than the other methods.

Infrared Small Target Detection Based on Weighted Improved Double Local Contrast Measure

The robust detection of infrared small targets plays an important role in infrared early warning systems. However, the high-brightness interference present in the background makes it challenging. To solve this problem, we propose a weighted improved double local contrast measure (WIDLCM) algorithm in this paper. Firstly, we utilize a fixed-scale three-layer window to compute the double neighborhood gray difference to screen candidate target pixels and estimate the target size. Then, according to the size information of each candidate target pixel, an improved double local contrast measure (IDLCM) based on the gray difference is designed to enhance the target and suppress the background. Next, considering the structural characteristics of the target edge, we propose the variance-based weighting coefficient to eliminate clutter further. Finally, the targets are detected by an adaptive threshold. Extensive experimental results demonstrate that our method outperforms several state-of-the-art methods.

Quasi-real-time earthquake relocation and monitoring in the northeastern Noto Peninsula

The seismicity rate markedly increased in the northeastern Noto Peninsula of Ishikawa Prefecture around the end of 2020, with an Mw6.2 event on 5 May, 2023, followed by many aftershocks. Previous earthquake relocation studies have detected upward migration of microearthquakes via multiple faults and clusters, suggesting the involvement of crustal fluids in this sequence. Since some active faults exist near the source region, there was concern that this sequence could lead to a larger earthquake; it became a reality with the Mw7.5 earthquake on 1 January 2024. This study aims to develop an algorithm to precisely relocate microearthquake hypocenters in quasi-real time for better monitoring. A fine view of seismicity requires relative relocation methods such as the double-difference (DD) method with numerous arrival time difference data precisely measured by the waveform correlation analysis. However, the standard DD method has the disadvantage of huge computational costs when data increase, making it unsuitable for real-time monitoring in such situations. We developed a quasi-real-time algorithm that relocates only new earthquakes using the DD method each time a new time window of data is added. The major improvement is that our method incorporates a traditional simple relative relocation and preserves constraints between different time windows; the relative locations of new events are constrained from reference events that were already relocated in the previous time windows. We tested a daily relocation algorithm on 11,546 events from 19 June, 2022, to 31 May, 2023, in the Noto Peninsula earthquake sequence. We found that our modification substantially reduced artificial hypocenter offsets between different time windows and succeeded in resolving the fine fault structures from the cloud-like distribution of initial hypocenters. If we do not impose constraints between different windows, the relocated hypocenters are scattered and do not show fine planar structures. Our algorithm greatly reduces the computational cost, allowing for quasi-real-time earthquake relocation and monitoring. We hope this algorithm will help monitor the spatio-temporal distribution of future earthquake sequences.Graphical

Research on the influence of green finance policy on enterprise green innovation

At present, China's economy has entered a new normal, and policies with economic growth as the core can no longer meet the needs of social development. In recent years, China has vigorously promoted the green transformation of economic development, and the construction of a green innovation system has become the only way to improve the ecological environment and promote green development. Green finance, as a financial tool providing services for green industries such as energy conservation, emission reduction and pollution prevention and control, plays an important role in the process of economic green transformation. Green Finance Reform and Innovation Pilot Zone is the latest practice of green finance policy system construction. Under this background, this paper takes the establishment of our country’s Green Finance Reform Innovation Experimental Zone as a quasi-natural experiment, and adopts the panel data of Shanghai and Shenzhen A-share listed companies from 2011 to 2022, this paper discusses the impact of Green Finance Policy on enterprise green innovation by means of multi-period double difference model. The study found that the policy has an obvious driving effect on enterprise green innovation, and the conclusion passed the parallel trend test and placebo test; in addition, the mechanism test results show that the stronger the financing constraints, the promotion effect of green financial innovation policy may weaken.

Coordinated Regional Economic Development: A Study of the Relationship Between Regional Policies and Business Performance

Abstract In the context of the global spread of the Corona Virus Disease 2019, improving enterprise performance, promoting regional economic development, and solving the problem of unbalanced and inadequate regional development are important considerations for regional policy formulation. To understand the relationship between regional policies and corporate performance, this study starts with theories related to regional policies and corporate performance, and proposes two hypotheses. The Western Development, Northeast Revitalization of the Old Industrial Base, and Central Rise Plan are selected as typical representatives of regional policies, and the hypotheses are verified through a double difference model. The results showed that regional policies could improve corporate performance, especially for state-owned enterprises (SOEs). The correlation between the revitalization of the old industrial base in Northeast China and the performance of SOEs was strong, with a correlation coefficient of 0.832. When conducting robustness tests by changing time periods, the correlation values between the performance of SOEs and policies in the three policy implementation areas of revitalizing Northeast China, western development, and central rise were 0.887, 0.764, and 0.652, respectively. Compared to non-SOEs, SOEs had a more significant effect on regional policy improvement. This conclusion was consistent with the empirical results of hypotheses 1 and 2. Based on this foundation, recommendations are offered for the suitability of regional policies to furnish theoretical frameworks for enhancing the regional policy structure and augmenting the precision and inclusivity of regional policy development. The research model is utilized to reveal the important role of regional policies in promoting enterprise performance improvement and promoting regional economic development. It can provide strong evidence support for policy makers. The study offers a scientific theoretical basis and empirical support that assist policymakers in comprehending policy objectives and implementation strategies with greater precision. Therefore, the coordinated advancement of regional economic development is facilitated.

Impact Study of Environment Public Interests Litigation on Carbon Emissions: Taking Pilot Policy of Procuratorial Public Interest Litigation as a Quasi-Natural Experiment

The environmental problems caused by carbon emission have become the focus of worldwide attention. Effective control of carbon emissions cannot be achieved without the protection of the rule of law. Environment public interests litigation is a prominent innovation in the judicial system, and its role in supervising the government to perform its regulatory duties on carbon reduction and regulating the carbon emission behaviors of enterprises and the public deserves discussion. The paper selected the panel data from 274 prefecture-level cities from 2013 to 2021 and analyzed the impact of a procuratorial public interest litigation pilot policy on carbon emission control by using the double difference method. The research found that the procuratorial public interest litigation pilot policy can effectively curb carbon emissions. Heterogeneity analysis showed that in cities with relatively low level of green innovation, the negative correlation between procuratorial public interest litigation pilot policies and carbon emissions is more significant. Compared with the eastern region, in the central and western regions, especially in the central region, where the concept, policy, and funding of carbon emission governance are relatively weak, the implementation of the pilot policy of procuratorial public interest litigation had a more obvious effect on carbon emission governance. Mechanism tests showed that procuratorial public interest litigation policies reduce carbon emissions by reducing energy consumption and increasing public participation in environmental protection. The study will provide an empirical basis for the carbon emission reduction effect on pilot policy of procuratorial public interest litigation and will offer certain theoretical recommendations for improving the procuratorial public interest litigation system in the ecological environment field.

3-D P-wave velocity structure of the upper mantle beneath eastern Indonesia from body wave tomography

Eastern Indonesia's tectonic setting is well known for its complexity and intense seismic activity. Controlled by several major and minor plates, including the Eurasian, Australian, and Pacific plates, this region is famous for its U-shaped subduction system beneath the Banda Arc. To better understand the architecture of the underlying structure in this region, we performed body-wave travel time tomography using ten years of catalog data provided by the Indonesian Agency for Meteorology, Climatology, and Geophysics. We utilize 9729 events in total, from which 46,446 P-wave arrival times were extracted. We used a double difference method to relocate the initial event catalog, which produced a pattern of seismicity consistent with a curved subduction system. Our tomographic model reveals a high velocity band between 90 and 240 km depth in the upper mantle, which is interpreted to be a concave dipping lithospheric slab that is parallel to the present-day Banda arc. Our results also show that lithosphere subducting from the north and south starts to collide at a depth of 300–350 km and becomes shallower further east. Apparent discontinuities in the high velocity band and a corresponding lack of seismicity supports the presence of a slab tear to the west of Seram. A dipping high velocity structure that is present from south to north beneath the island of Timor represents a subducting slab that dips more steeply beyond a depth of 150–200 km, which appears consistent with slab roll-back. Our tomographic model also shows evidence of back arc thrusting to the north of Sumbawa and Flores Islands in the form of a south-dipping higher velocity band at shallow depth. Furthermore, our tomographic models also reveal the possible presence of underthrust continental forearc in the form of a thin higher velocity anomaly that connects the backarc thrust and northward dipping lithosphere slab in the Timor area. Finally, a zone of low velocity above the higher velocity slab is clearly seen beneath Seram Island at a depth of ∼100 km and may represent a partial melting zone.

The Impact of Housing Market Regulation Policies on the Housing Choice Behavior of Urban Residents

Abstract Housing is a social and developmental issue of public concern, which is related to the personal interests of every household and the people’s “living in a home”. The article quantifies the housing choice behavior of urban residents by the ring index of residential housing purchase price, and solves the problem of sample selection error by using the propensity to match score to match the experimental group and the control group. A double difference model is used to analyze the net effect of the implementation of housing market regulation policies on urban residents’ housing choice behavior. Parallel trend test in the experimental and control groups before and after the implementation of housing market regulation policies in 2018 shows significant differences, the ATT value of HSB after propensity score matching is positive, and the sample mean of the control group is 0.452 lower than that of the experimental group. The coefficient of the effect of housing market regulation policies on the behavior of urban residents’ housing choices is 0.351 and shows significance at the 1% level. The active implementation of housing market regulation policy can help optimize the housing purchase price index, which in turn stimulates the housing choice behavior of urban residents and promotes the stable and healthy development of the housing market.

Promotion Effects of High-Speed Rail on Urban Development: Evidence from Three Lines in China

Amid the vigorous development of the high-speed rail (HSR) network, local governments in China generally consider the construction of HSR as a crucial task in their regional development strategies. Currently, most provincial capitals and prefecture-level cities in the eastern and central regions of China already have operational HSR services. This study aims to examine a key question: has the objective of local governments to promote urban development through the construction of HSR been effective? The research selects cities along the Beijing–Shanghai, Beijing–Guangzhou, and Harbin–Dalian HSR lines as the study subjects. Based on the principles of proximity and similarity, cities with operational HSR and those without are chosen as the experimental group and the control group, respectively. Following the double difference (difference-in-differences) approach, an advantage index is proposed to systematically evaluate the impact of HSR operation on urban development from three dimensions: population aggregation, economic development, and expansion of construction land. Furthermore, the evaluation results are systematically clustered to identify city types that exhibit different promotional effects in various dimensions. The research findings indicate the following: (1) The promotion effect of HSR on the development of small to medium-sized cities is more reflected in economic growth and construction land growth. (2) The promotion effect of HSR on the development of large cities is more reflected in the growth of the employment population. (3) For smaller or economically less-developed cities, HSR may be detrimental to the aggregation of resident and employment populations. (4) Cities with moderate size and good economic development have the opportunity to use HSR to promote population aggregation. On this basis, combined with the findings above, strategies to promote the coordinated development of high-speed rail construction and urban systems are discussed.

Unveiling complex fault geometry and driving mechanisms: insights from a refined data processing and multiplet analysis of the 2010 Beni-Ilmane seismic sequence (NE Algeria)

SUMMARY This paper offers a comprehensive re-analysis of the Beni-Ilmane 2010 seismic sequence, using a data set that is 100 per cent larger than previous studies. This unprecedented sequence in Algeria features three main shocks with magnitudes Mw 5.4, 5.1 and 5.1. Our approach involves high-precision relocation, which includes the development of a new 1-D minimum velocity model, followed by a double-difference (DD) procedure and hierarchical clustering. We determined the focal mechanisms (FMs) for 128 key events and identified 21 multiplet groups using an average cross-correlation threshold of 0.8. Our analysis offers new insights into fault geometry and addresses ongoing debates, by proposing a seismotectonic model that reveals the activation of 14 fault segments during the sequence, in contrast to previous oversimplified models that suggested two or three faults. The computed stress field from the inversion of 128 FMs aligns with a tectonic loading force due to the convergence of the African and Eurasian plates. These findings highlight the complexity of the fault network in the study area and shed light on the role of strike-slip faults in shaping the thrust belt. We found a strong link between multiplet groups and fluid movement along the fault network. Analysis of the temporal history of these multiplet groups provides new insights into fluid dynamics timescales, with an estimated hydraulic diffusivity (D) of 0.36 m2 s−1 suggesting a fluid pressure diffusion process. The observed expansion of the aftershock area with the logarithm of time and the existence of repeating earthquakes indicates, for the first time, an aseismic slip mechanism that adds an additional layer to the driven processes. In conclusion, our results suggest that the underlying mechanisms governing the BI-2010 seismic sequence involve a complex interplay of tectonic loading, coseismic stress transfer, fluid dynamics and aseismic slip transients. We attempt to correlate our findings with various studies linking the structure, mechanics and fluid flow properties of fault zones and fault systems. The activation of smaller fault segments potentially averted a larger quake, resulting in three moderate main shocks and numerous aftershocks. This work not only enrich our understanding of seismic phenomena but also provides useful insights for seismic hazard assessment and risk mitigation strategies.

Accuracy and reliability improved GNSS partial ambiguity resolution assisted by a MEMS inertial measurement unit

Traditional partial ambiguity resolution (PAR) methods based on integer least-squares (ILS-PAR) assume that the ambiguity terms are unbiased integers, which is seldomly true in challenging environments of the Global Navigation Satellite System (GNSS). The bias will lead to unreliable positioning solutions. This study proposes a reliable PAR method based on the tightly coupling of GNSS and inertial navigation system (INS) and the solution separation with external solution (SSE) statistical testing algorithm. First, the inertial measurement unit (IMU) mechanization results are compensated using the latest fixed real-time kinematic (RTK) solutions, thus high-accuracy INS predictions are obtainable at the current GNSS epoch. Second, the SSE method based on double-differenced (DD) carrier-phase measurements are applied to select and validate the ambiguity subset and perform the GNSS/INS integration. A dynamic vehicular experiment with a low-cost microelectromechanical systems (MEMS) device has been conducted and the results indicate that the proposed method can ensure good performance of both accuracy and reliability.