US-built early-warning radar helped Taiwan spot China’s submarine-launched ballistic missile 7%

By Jijo Malayil30%

7/10/2026, 1:51:42 PM

BS Summary: This article contains 13 faulty reasoning types, including Unattributed Quote, Halo Effect, and Overconfidence Bias, with Appeal to Authority as the most egregious example at 26.6% saturation with 148 hits. Analysis detected 569 faulty-reasoning hits from 556 analyzed words, generating a BS Score of 23.7% and a BS Rank of 7% (20,359 of 21,887 articles). This article is better (less manipulative) than 93.00% of the article peer group.

A long-range early-warning radar in Taiwan tracked China’s recent ballistic missile launch. 
Named AN/FPS-115 Pave Paws, the radar tracked the missile shortly after it was fired from a nuclear-powered submarine in the South China Sea. 
The radar, located at Leshan Radar Station in Hsinchu County, monitored the missile during the initial phase of its flight while it remained within the system’s coverage, according to online media outlets. 
The detection, combined with intelligence sharing with the US, provided Taipei with critical information about the launch, highlighting the radar’s strategic early-warning capabilities. 
Early warning radar 
Taiwan’s long-range AN/FPS-115 Pave Paws early-warning radar tracked China’s recent ballistic missile launch shortly after it was fired from a nuclear-powered submarine in the South China Sea, providing Taipei with critical data on the missile’s trajectory, according to a senior Taiwanese official. 
The official, quoted by Taiwan’s Liberty Times , said the US-made radar detected the missile soon after launch and monitored it during the initial phase of its flight while it remained within the system’s coverage. 
Taiwan also shared the tracking data with the United States, which continued monitoring the missile using satellites and long-range early-warning radars after it moved beyond the radar’s range, reports the South China Morning Post (SCMP). 
The launch was part of a Chinese ballistic missile test announced earlier this week. 
Beijing has described the test as a routine military exercise but has not disclosed the type of missile used or its exact flight path. 
Taiwan’s National Security Council Secretary General Joseph Wu later shared a map on social media showing what he said was the missile’s trajectory. 
According to the map, the missile was launched from waters near China’s southern coast, flew over the northern Philippines, and landed in international waters between Nauru and Tonga. 
Wu identified the missile as a JL-2 submarine-launched ballistic missile, although Chinese authorities have not confirmed that assessment. 
Military analysts have debated whether the test involved the JL-2 or the newer, longer-range JL-3 submarine-launched ballistic missile, reports SCMP . 
Taiwan’s missile shield 
The AN/FPS-115 Pave Paws radar is located at Leshan Radar Station in Hsinchu County in northern Taiwan. 
Developed by US defense contractor Raytheon and operational since 2013, the system is a key element of Taiwan’s missile early-warning network. 
The radar uses a fixed active phased-array antenna to continuously scan large areas without mechanical rotation, enabling rapid detection and tracking of multiple targets simultaneously. 
Taiwan’s upgraded version can also detect low-altitude cruise missiles, tactical ballistic missiles, aircraft, and other airborne threats. 
Positioned at an elevation of about 2,600 meters, the radar can reportedly detect ballistic missile launches at distances of up to 3,106 miles (5,000 kilometers). 
Its coverage extends across mainland China, the South China Sea, and the Korean Peninsula. 
Taiwan’s version of the system has also been upgraded to improve its ability to detect low-altitude cruise missiles and tactical ballistic missiles, reports the Economic Times . 
Taiwanese officials have previously said the radar has monitored People’s Liberation Army missile launches into waters east of Taiwan, underscoring its role in tracking regional military activity. 
The incident also highlighted intelligence cooperation between Taiwan and the US. 
According to the Taiwanese official, Taipei provided initial tracking information before US satellite and radar assets took over monitoring during the missile’s later flight, reports SCMP. 
Article reasoning-pattern comparisonThis article: 5.0%Jijo Malayil: 5.0%Interesting Engineering: 3.9%Confirmation Bias5.0%This article: 0.0%Jijo Malayil: 0.4%Interesting Engineering: 1.2%Anchoring Bias0.0%This article: 0.0%Jijo Malayil: 1.7%Interesting Engineering: 2.4%Availability Heuristic0.0%This article: 0.0%Jijo Malayil: 1.7%Interesting Engineering: 1.2%Representativeness Heuristic0.0%This article: 0.0%Jijo Malayil: 0.7%Interesting Engineering: 0.3%Hindsight Bias0.0%This article: 7.7%Jijo Malayil: 2.4%Interesting Engineering: 5.2%Overconfidence Bias7.7%This article: 2.5%Jijo Malayil: 3.1%Interesting Engineering: 6.4%Framing Effect2.5%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.2%Loss Aversion0.0%This article: 4.7%Jijo Malayil: 0.5%Interesting Engineering: 0.6%Status Quo Bias4.7%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.5%Sunk Cost Effect0.0%This article: 3.1%Jijo Malayil: 6.9%Interesting Engineering: 16.9%Optimism Bias3.1%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.6%Pessimism Bias0.0%This article: 0.0%Jijo Malayil: 0.2%Interesting Engineering: 0.9%Negativity Bias0.0%This article: 4.9%Jijo Malayil: 1.5%Interesting Engineering: 4.6%Self-Serving Bias4.9%This article: 0.0%Jijo Malayil: 0.3%Interesting Engineering: 0.2%Fundamental Attribution Error0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Actor-Observer Bias0.0%This article: 0.0%Jijo Malayil: 1.8%Interesting Engineering: 0.9%In-Group Bias0.0%This article: 0.0%Jijo Malayil: 0.4%Interesting Engineering: 0.1%Out-Group Homogeneity Bias0.0%This article: 7.9%Jijo Malayil: 6.0%Interesting Engineering: 5.2%Halo Effect7.9%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Horn Effect0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Dunning-Kruger Effect0.0%This article: 3.8%Jijo Malayil: 1.0%Interesting Engineering: 1.1%Recency Bias3.8%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.2%Primacy Effect0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Blind-Spot Bias0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Ad Hominem0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Straw Man0.0%This article: 26.6%Jijo Malayil: 15.5%Interesting Engineering: 8.6%Appeal to Authority26.6%This article: 0.0%Jijo Malayil: 1.1%Interesting Engineering: 1.5%False Dilemma0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.3%Slippery Slope0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.1%Circular Reasoning0.0%This article: 0.0%Jijo Malayil: 4.3%Interesting Engineering: 5.1%Hasty Generalization0.0%This article: 0.0%Jijo Malayil: 0.9%Interesting Engineering: 0.1%Red Herring0.0%This article: 0.0%Jijo Malayil: 0.7%Interesting Engineering: 0.8%Bandwagon0.0%This article: 0.0%Jijo Malayil: 0.3%Interesting Engineering: 2.3%Appeal to Emotion0.0%This article: 0.0%Jijo Malayil: 0.9%Interesting Engineering: 1.2%Begging the Question0.0%This article: 0.0%Jijo Malayil: 2.0%Interesting Engineering: 2.2%Post Hoc (False Cause)0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Tu Quoque0.0%This article: 0.0%Jijo Malayil: 1.8%Interesting Engineering: 0.6%Burden of Proof0.0%This article: 0.0%Jijo Malayil: 0.6%Interesting Engineering: 0.2%Appeal to Nature0.0%This article: 0.0%Jijo Malayil: 0.1%Interesting Engineering: 0.3%Composition/Division0.0%This article: 0.0%Jijo Malayil: 0.1%Interesting Engineering: 0.7%Anecdotal0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.1%No True Scotsman0.0%This article: 5.0%Jijo Malayil: 4.9%Interesting Engineering: 2.6%Ambiguity (Equivocation)5.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Jijo Malayil: 0.1%Interesting Engineering: 0.1%Middle Ground0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Personal Incredulity0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.1%Special Pleading0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Genetic Fallacy0.0%This article: 18.5%Jijo Malayil: 2.4%Interesting Engineering: 1.7%Unattributed Quote18.5%This article: 6.3%Jijo Malayil: 0.4%Interesting Engineering: 0.7%Quote-first Misdirection6.3%This article: 6.3%Jijo Malayil: 5.1%Interesting Engineering: 3.9%Biased Writer Voice6.3%This article: 0.0%Jijo Malayil: 1.0%Interesting Engineering: 0.7%Indoctrination0.0%This article: 0.0%Jijo Malayil: 0.0%Interesting Engineering: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Jijo Malayil: 0.2%Interesting Engineering: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Jijo Malayil: 4.0%Interesting Engineering: 10.7%Attempt to Sell a Product or S…0.0%

556 words analyzed.

Speakers

4speakers27%attributed speech406writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 35 words • 100.0% coverageSouth China Morning Post (SCMP) • 35 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageJoseph Wu • 23 words • 100.0% coverageWriter's voice • 28 words • 0.0% coverageJoseph Wu • 18 words • 0.0% coverageSCMP • 21 words • 100.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageEconomic Times • 27 words • 0.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageSCMP • 26 words • 0.0% coverage
Selected voice

SCMP

100%flagged-word coverage
47 attributed words31% of attributed speech65% writer coverage
0%22.5%45.0%Unattributed Quote+30.1 ptsWriter: 14.5%SCMP: 44.7%44.7%Quote-first Misdirection-8.6 ptsWriter: 8.6%SCMP: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.