The level of automation of land vehicles has been constantly enhanced by the introduction of new sensors, innovative algorithms, and systems integration in meeting the increasing demand of safety, efficiency, and convenience. For the navigation of a vehicle, a GNSS receiver, vehicular sensors, and inertial measurement units are often employed to provide a fused navigation solution in various environments. These sensors are known to be complementary and the fused solution is known to be able to provide a better accuracy, integrity, and availability. More recently, vehicles are often equipped with camera, radars, ultra sonic sensors, and lidars to provide advanced driver assistant functions or even autonomous driving features. In practice, it may be desired to seek a flexible design framework to host various sensors so that the contributions of different sensors can be assessed. Moreover, it may also be desired to augment an existing sensor suite with some add-on sensors to enhance performance. To realize the above objectives, a plug-andplay ROS-based navigation suite is presented. ROS, standing for Robot Operating System is an open-source, meta operating system that was initially developed for robotic research with the desire of sharing and collaboration in mind. Such a framework turns out to be very beneficial in navigation suite design as different types of sensors with different data messages and data rates can be accommodated and fused. The paper discusses the setup of an ROS-based vehicular navigation suite, presents the information filtering algorithm to facilitate the plug-andplay feature, and demonstrates the effectiveness of the ROS-based navigation suite in terms of performance and reconfigurability.