RSS And AoA Based Target Localization For Wireless Sensor Networks

Location-based services have been a prerequisite for wireless network communication.In the 21 st century,with the advent of the information age in which all things are connected,location-based service-related information plays an irreplaceable role in navigation,logistics,fire protection,security and other fields.Location without specific location will be futile and unproductive in the modern developing society.The key to obtaining a precise target location depends on the wireless positioning technologies.Thus,the research of wireless positioning technologies has become a new guidance for the development.Peoples were aware about the positioning technologies because of global positioning system(GPS).In the late 20 th century,GPS and Bei Dou Navigation Satellite System(BDS)enabled wireless positioning technologies to serve better for the mankind.The satellite navigation system provides global users with high-precision positioning and navigation services in any time and under any weather condition,and also highlights the development direction for the wireless positioning technologies.Both GPS and BDS can only obtain the target's outdoor location information,which can basically meet the vast majority of needs in the outdoor environments.However,in densely populated urban environments,indoor environments,forests,underground areas,the signal is extremely weak,which makes it difficult and sometimes impossible to obtain the location information of the target.In addition,in underwater environment,sound waves are the only reliable carrier for signal transmission,which causes the satellite positioning system unavailable.Therefore,in such environments,research on the location of Wireless Sensor Networks(WSNs)is quite necessary.WSNs localization techniques based on measurement information are used to determine the target location.These measurements mainly include Time-of-Arrival(To A),Time-Difference-of-Arrival(TDo A),Received Signal Strength(RSS),Angle-of-Arrival(AoA)and their combination.The localization problems based on these measurements information are,however,highly non-linear and non-convex,making it difficult to get an effective solution.In order to solve this problem effectively,the relaxation technique of convex optimization is used to transform the above-mentioned problems into a convex problem,and obtains the approximate optimal solution of the original problems.More specifically,the main innovations of this paper include the following aspects:1)For the RSS-based localization problem under the background of independent and uncorrelated Gaussian noise,a mathematical model of the target location optimization based on MLcriterion is established,and then the original non-convex optimization problem is transformed into a Semi-Definite Programming(SDP)problem by using relaxation technique,thus an effective solution algorithm is proposed.Computer simulation results show that the proposed algorithm has high positioning accuracy and the performance is closer to Cramer-Rao Lower Bound(CRLB).2)For the RSS-based localization problem under the background of correlated Gaussian noise,firstly,based on the RSS measurement model and WLS criterion,the minimum optimization problem for solving the target location is constructed.Secondly,by using the equivalence between norms,the logarithm of the objective function in the constructed optimization problem is removed.Then,the optimization problem is transformed into a convex problem to be solved effectively by using the relaxation techniques of SOCP and SDP.Both theoretical derivation and simulation experiments illustrate that the proposed algorithm has high positioning accuracy,performance close to CRLB,and has good performance even in high noise environment.3)A new positioning method based on WLS in the case of known and unknown transmit power is proposed for the collaborative positioning based on RSS.Firstly,the RSS based cooperative positioning is constructed as an approximate WLS minimum estimation problem,and then the SOCP relaxation technique is used to approximate the optimal solution of the original target position.Furthermore,when the transmit power is unknown,the reference power is also treated as an unknown parameter.In order to improve the positioning accuracy,the estimated position is taken as initial solution,and an alternating estimation algorithm of mixed ML and SOCP is proposed.This algorithm further improves the accuracy of cooperative positioning based on RSS.4)For the localization problem based on the RSS and AoA mixed measurement,a new optimization algorithm with known and unknown transmit power is proposed respectively.In known transmit power case,by using the polarized identity and transforming available AoA measurements into distance forms,a new relationship between the target location and AoA measurements is established.Then a WLS non-convex optimization problem for the target location is constructed.Moreover,the approximate solution of the target position is obtained by using both SOCP and SDP relaxation techniques.In unknown transmit power case,the unknown transmission power is also treated as unknown parameter.By using the mean inequality,the localization method and implementation algorithm in unknown transmit power are designed.The simulation results show that the proposed algorithm can improve the accuracy of localization in both the known and unknown transmit power cases.5)For the RSS-based localization problem in underwater wireless sensor networks,a Generalized Trust Region Subproblem(GTRS)method is proposed.This method is a low-complexity algorithm for approximating the global optimal solution of non-convex ML estimation problem.In addition,in order to further verify the performance of the algorithm,the CRLB is derived for the RSS-based localization problem in underwater wireless sensor networks.Compared with other existing methods,this method has lower complexity and the localization performance is closer to CRLB.6)Finally,for the non-linear transmission characteristics of signals in Underwater Acoustic Wireless Sensor Networks(UWSNs),the localization problem based on RSS is developed,and a convex optimization localization method is proposed.Firstly,the ray model of underwater acoustic propagation is analyzed,then a WLS minimum optimization problem is formed by using the model approximation.Secondly,the underwater RSS model is given and further approximated,then the WLS minimum optimization problem is constructed.Finally,the global optimal solution of the target location is approximated by using SOCP and SDP.Furthermore,CRLB is also derived.The effectiveness to achieve better accuracy of the proposed methods is verified through theoretical derivation and computer simulation experiments.