Global navigation satellite system (GNSS) receivers are ubiquitous in our society, and because they are vulnerable to jamming attacks, it is important to quickly detect and localize any attackers. Instead of relying on dedicated sensing infrastructure for localization, one can utilize crowdsensing, or participatory sensing, where a large ensemble of users contributes measurements. In this work, the used measurements are carrier-to-noise-density ratio (C/N0) estimates and automatic gain control (AGC) values, which can both be retrieved from commercial connected GNSS receivers such as mobile phones. We extend our localization algorithm, with the option to use AGC values or C/N0 estimates alone or in combination, and improve the convergence rate. The flexibility of the proposed algorithm in using either AGC or C/N0 data, depending on the type of phone, increases the potential of the algorithm for participatory localization. The proposed algorithm was evaluated using data from different types of mobile phones in a simulated environment and in over-the-air field tests. These evaluations show that the proposed algorithm can operate in real-world situations and that it outperforms similar localization algorithms, achieving an estimated error of approximately 50-60 m for a free line-of-sight path loss. Moreover, for a varying path loss, the error remains well below 500 m most of the time. Given that the receivers are placed up to over 5000 m from the transmitter, these results show that the proposed localization algorithm is efficient in narrowing down the jammer position. Based on this localization, a report to relevant authorities can be facilitate further action, e.g., precise localization and removal of the jammer.